WO2024128101A1 - Image processing method, image processing device, image processing system, and program - Google Patents

Image processing method, image processing device, image processing system, and program Download PDF

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Publication number
WO2024128101A1
WO2024128101A1 PCT/JP2023/043708 JP2023043708W WO2024128101A1 WO 2024128101 A1 WO2024128101 A1 WO 2024128101A1 JP 2023043708 W JP2023043708 W JP 2023043708W WO 2024128101 A1 WO2024128101 A1 WO 2024128101A1
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image
voids
image processing
unit
processing method
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PCT/JP2023/043708
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French (fr)
Japanese (ja)
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裕子 新田
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コニカミノルタ株式会社
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Publication of WO2024128101A1 publication Critical patent/WO2024128101A1/en

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N23/00—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00
    • G01N23/02—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by transmitting the radiation through the material
    • G01N23/04—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by transmitting the radiation through the material and forming images of the material
    • G01N23/041—Phase-contrast imaging, e.g. using grating interferometers
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N23/00—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00
    • G01N23/02—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by transmitting the radiation through the material
    • G01N23/06—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by transmitting the radiation through the material and measuring the absorption
    • G01N23/18—Investigating the presence of flaws defects or foreign matter

Definitions

  • the present invention relates to an image processing method, an image processing device, an image processing system, and a program.
  • Patent Document 1 discloses a method for detecting defects in a fiber-reinforced resin.
  • the defect detection method described in Patent Document 1 aims to see the extent of defects in the molded fiber-reinforced resin, and therefore treats all black streaks that appear in the captured image as defects. Therefore, the defect detection method described in Patent Document 1 does not detect information on what the defect is based on (e.g., poor impregnation, cracks, delamination), and the detected defect information is insufficient for designing fiber-reinforced resins.
  • the present invention therefore aims to provide an image processing method, image processing device, image processing system, and program that can output more detailed information about defects in a subject that contains fibers and resin.
  • the image processing method of the present invention comprises the steps of: 1.
  • An image processing method for an image obtained by photographing an object containing fibers and resin with an X-ray Talbot imaging device comprising: an image acquisition step of acquiring a reconstructed image based on the image; an extraction step of extracting a defect in the object based on the reconstructed image; a determining step of determining a type of void contained in the defect; an output step of outputting information about the determined voids; has.
  • the image processing device of the present invention further comprises: An image processing device for processing an image obtained by photographing an object containing fibers and resin with an X-ray Talbot imaging device, comprising: an image acquisition unit for acquiring a reconstructed image based on the image; an extraction unit that extracts defects in the object based on the reconstructed image; A discrimination unit that discriminates the type of void contained in the defect; an output unit that outputs information about the determined voids; Equipped with.
  • the image processing system of the present invention further comprises: An image processing system including an X-ray Talbot imaging device and a server,
  • the X-ray Talbot device comprises: an imaging unit that images an object containing fibers and a resin; an image acquisition unit for acquiring a reconstructed image based on the captured image; a first transmission unit that transmits the reconstructed image to the server; an information receiving unit that receives information regarding voids included in the reconstructed image from the server; an output unit that outputs information about the void; Equipped with The server, an extraction unit that extracts defects in the object based on the reconstructed image; A discrimination unit that discriminates the type of void contained in the defect; a second transmission unit that transmits information about the determined void to the X-ray Talbot device; Equipped with.
  • the program of the present invention is A computer of an image processing device for an image obtained by photographing an object containing fibers and resin with an X-ray Talbot imaging device, an image acquisition unit for acquiring a reconstructed image based on the image; an extraction unit that extracts defects in the object based on the reconstructed image; A discrimination unit that discriminates the type of void contained in the defect; an output unit that outputs information about the determined voids; Function as.
  • the present invention makes it possible to output more detailed information about defects in subjects that contain fibers and resin.
  • FIG. 1 is a schematic diagram showing an overall view of an X-ray Talbot imaging device.
  • FIG. 1 is a diagram illustrating the principle of a Talbot interferometer.
  • 3 is a schematic plan view of a source grating, a first grating, and a second grating.
  • FIG. 2 is a block diagram showing a functional configuration of the image processing device.
  • 13 shows examples of a differential phase image, a scattering intensity image, and an absorption image.
  • a three-dimensional view of the subject and the shooting direction. 13 is an example of void detection using a 2D transmission image.
  • 1 is an example of a differential phase image. 1 shows examples of voids and foreign matter in differential phase images.
  • FIG. 13 is an example of the transition of signal values in a void portion and a foreign substance portion. 13 is a flowchart showing image processing. This is an image of how fibers, resin, and voids appear in each image.
  • FIG. 1 is an image diagram of area A and area B.
  • FIG. 13 is a schematic diagram showing discrimination using only small-angle scattering images.
  • FIG. 13 is a schematic diagram showing discrimination using only small-angle scattering images.
  • 1 is a graph showing the relationship between void particle size and small-angle scattering signal intensity.
  • FIG. 2 is a block diagram showing a functional configuration of the X-ray imaging system.
  • FIG. 1 is a schematic diagram showing an overall view of a three-dimensional Talbot imaging device. 1 is a diagram illustrating the principle of a three-dimensional Talbot interferometer.
  • an X-ray imaging system 100 of this embodiment includes an X-ray Talbot imaging device 1 and an image processing device 2.
  • the X-ray imaging system 100 rotates the subject H (inspection object) or the grid in a plane perpendicular to the optical axis of the X-rays using the X-ray Talbot imaging device 1 to change the relative angle and capture the image multiple times.
  • the image processing device 2 generates a reconstructed image for each imaging angle based on the moire image read by the X-ray Talbot imaging device 1 and a moire image in a state where the subject H does not exist (referred to as a BG: Back Ground moire image).
  • the X-ray imaging system 100 captures a moire image in a state in which the subject H is not present at least once before or after the imaging of the subject H.
  • the X-ray Talbot imaging device 1 uses a Talbot-Lau interferometer equipped with a source grating (also called G0 grating) 12. It is also possible to use an X-ray Talbot imaging device that does not have a source grating 12 and uses a Talbot interferometer equipped only with a first grating (also called G1 grating) 14 and a second grating (also called G2 grating) 15.
  • a source grating also called G0 grating
  • G1 grating also called G1 grating
  • G2 grating also called G2 grating
  • the object to be inspected in this embodiment is made of a composite material (also called a composite material) and is used as a component part of a variety of products, including aerospace and aircraft related products, automobiles, ships, fishing rods, as well as electrical, electronic and home appliance parts, parabolic antennas, bathtubs, flooring materials, roofing materials, etc.
  • composite materials include CFRP (Carbon-Fiber-Reinforced Plastics) and CFRTP (Carbon Fiber Reinforced Plastics) that use carbon fiber or glass fiber as reinforcing fibers.
  • FRPs Fiber-Reinforced Plastics
  • CFRP Carbon Fiber Reinforced Thermo Plastics
  • GFRP Glass Fiber Reinforced Plastics
  • CMCs Ceramic Matrix Composites
  • the resins used in the composite materials are, for example, general-purpose plastics, engineering plastics, and super engineering plastics, but are not limited to these.
  • Resins are used as resin composite materials to which fillers having micro- or nano-sized structures are added to impart certain properties such as strength, and are often used as plastic molded products.
  • Fillers include organic materials, inorganic materials, magnetic materials, and metal materials.
  • PPS, POM, PA, PC, PP, etc. may be used as resins, and aramid fibers, talc, cellulose fibers, etc. may be used as fillers.
  • nylon may be used as resins, and strontium ferrite, samarium cobalt, etc. may be used as fillers.
  • the above-mentioned composite materials are manufactured as molded products by pouring resin into a mold (injection molding) or by extruding resin into a sheet.
  • the subject H may be the molded product itself or a sample cut out from the molded product. Note that the subject H is not limited to molded products.
  • the X-ray Talbot imaging device 1 includes an X-ray generator 11, a source grating 12, a subject table 13, a first grating 14, a second grating 15, an X-ray detector 16, a support 17, and a base unit 18.
  • reconstructed images At least three types of images can be reconstructed (referred to as reconstructed images) by capturing a moire image of the subject H at a predetermined position relative to the subject table 13 using a method based on the principles of the fringe scanning method and analyzing the moire image using the Fourier transform method.
  • an absorption image (same as a normal X-ray absorption image) which visualizes the difference in average components between the BG moiré fringe image and the moiré fringe image; a differential phase image which visualizes the phase difference between the BG moiré fringe image and the moiré fringe image; and a small-angle scattering image which visualizes the visibility rate, which is the ratio of the visibility of the BG moiré fringe image and the moiré fringe image.
  • an absorption image standard as X-ray absorption image
  • a differential phase image which visualizes the phase difference between the BG moiré fringe image and the moiré fringe image
  • a small-angle scattering image which visualizes the visibility rate, which is the ratio of the visibility of the BG moiré fringe image and the moiré fringe image.
  • the fringe scanning method is a method in which one of multiple gratings is moved in the direction of the slit period by 1/M (M is a positive integer, M>2 for absorption images, M>3 for differential phase images and small-angle scattering images) of the grating, and then reconstructed using the moiré images captured M times to obtain a high-resolution reconstructed image.
  • M is a positive integer, M>2 for absorption images, M>3 for differential phase images and small-angle scattering images
  • the Fourier transform method is a method in which, in the presence of a subject, a single moiré image is captured using an X-ray Talbot imaging device, and then in image processing, the moiré image is subjected to a Fourier transform or other process to reconstruct and generate an absorption image, differential phase image, and small-angle scattering image.
  • Fig. 2 shows the case of a Talbot interferometer
  • the z direction in Fig. 2 corresponds to the vertical direction (z direction) in the X-ray Talbot imaging device 1 in Fig. 1
  • the x and y directions in Fig. 2 correspond to the horizontal directions (front-back and left-right directions) in the X-ray Talbot imaging device 1 in Fig. 1.
  • the first grating 14 and the second grating 15 (and also the source grating 12 in the case of a Talbot-Lau interferometer) have a plurality of slits S arranged in parallel with each other at a predetermined period d in the x direction perpendicular to the z direction, which is the irradiation direction of the X-rays.
  • the periods of the source grating 12, the first grating 14, and the second grating 15 are not limited to being the same.
  • X-rays irradiated from X-ray source 11a (X-ray generator 11) (in the case of a Talbot-Lau interferometer, the X-rays irradiated from X-ray source 11a are converted into multiple light sources by source grating 12 (not shown in Figure 2)) pass through first grating 14.
  • the transmitted X-rays then form images at regular intervals in the z direction. These images are called self-images (also called grating images, etc.), and the phenomenon in which self-images are formed at regular intervals in the z direction is called the Talbot effect.
  • the Talbot effect is a phenomenon in which, when coherent light passes through the first grating 14, which has slits S at a constant period d as shown in Figure 2, it forms self-images at constant intervals in the direction of light travel, as described above.
  • a second grating 15 having slits S with approximately the same period as the self-image of the first grating 14 is placed at the position where the self-image of the first grating 14 forms an image.
  • the extension direction of the slits S of the second grating 15 i.e., the x-axis direction in FIG. 2
  • a moiré image Mo is obtained on the second grating 15.
  • the moire image Mo is drawn away from the second grating 15 because if the moire image Mo were drawn on the second grating 15, the moire fringes and slits S would be mixed together and would be difficult to understand. However, in reality, the moire image Mo is formed on the second grating 15 and downstream of it. This moire image Mo is then captured by the X-ray detector 16, which is placed directly below the second grating 15.
  • the presence of the subject H between the X-ray source 11a (X-ray generating device 11) and the first grating 14 (i.e., on the subject table 13 in FIG. 1) causes a phase shift of the X-rays and scattering of the X-rays.
  • the phase shift of the X-rays causes the moire fringes of the moire image Mo to become distorted at the boundary of the subject's edge, and the scattering of the X-rays reduces the visibility rate of the scattered portion, not limited to the edge of the subject.
  • the subject H does not exist between the X-ray source 11a (X-ray generating device 11) and the first grating 14, a moire fringe image not influenced by the subject H, that is, a BG moire image, appears.
  • the above is the principle of the Talbot interferometer and the Talbot-Lau interferometer.
  • the first grating 14 may be disposed in front of the subject H (on the X-ray generating device 11 side).
  • the second grating 15 is arranged in the second cover unit 130 at a position where the self-image of the first grating 14 forms an image. Furthermore, since the moiré image Mo (see FIG. 2) becomes blurred when the second grating 15 and the X-ray detector 16 are separated, in this embodiment, the X-ray detector 16 is arranged directly below the second grating 15.
  • the second cover unit 130 is provided to protect the X-ray detector 16, etc. by preventing people or objects from colliding with or touching the first grating 14, second grating 15, X-ray detector 16, etc.
  • the X-ray detector 16 is configured such that conversion elements that generate electrical signals in response to irradiated X-rays are arranged in a two-dimensional array (matrix), and the electrical signals generated by the conversion elements are read as image signals.
  • the X-ray detector 16 captures the moiré image Mo, which is an image of the X-rays formed on the second grating 15, as an image signal for each conversion element.
  • the X-ray Talbot imaging device 1 captures multiple moiré images Mo using a so-called fringe scanning method. That is, in the X-ray Talbot imaging device 1 according to this embodiment, multiple moiré images Mo are captured while shifting the relative positions of the first grating 14 and the second grating 15 in the x-axis direction in Figures 1 to 3 (i.e., the direction perpendicular to the extension direction (y-axis direction) of the slit S). In another embodiment, the source grating 12 may be moved.
  • the image processing device 2 receives image signals of multiple moiré images Mo from the X-ray Talbot imaging device 1, and performs image processing to reconstruct an absorption image, a differential phase image, a small-angle scattering image, etc. based on the multiple moiré images Mo.
  • a moving device (not shown) is provided for moving the first grating 14 in the x-axis direction by a predetermined amount. Note that it is also possible to configure the device so that the second grating 15 is moved instead of the first grating 14, or so that both are moved. In another embodiment, the source grating 12 may be moved.
  • the X-ray Talbot imaging device 1 captures only one moire image Mo while keeping the relative positions of the first grating 14 and the second grating 15 fixed. Then, in image processing in the image processing device, this moire image Mo can be analyzed using a Fourier transform method or the like to reconstruct an absorption image, a differential phase image, and a small-angle scattering image.
  • a sine wave graph is a graph in which the horizontal axis represents the relative angle between the sample and the lattice, and the vertical axis represents the small-angle scattering signal value of a certain pixel. The amplitude, average, and phase of the sine wave are obtained as fitting parameters.
  • an image showing the amplitude value for each pixel is called an orientation degree image
  • an image showing the average value for each pixel is called a scattering intensity image
  • an image showing the phase for each pixel is called an orientation angle image.
  • the fitting method is not limited to a sine wave.
  • the term "reconstructed image” will also refer to orientation analysis images (orientation degree image, scattering intensity image, and orientation angle image) generated by recombining the reconstructed images.
  • the device is a so-called vertical type, and the X-ray generator 11, the radiation source grating 12, the subject table 13, the first grating 14, the second grating 15, and the X-ray detector 16 are arranged in this order in the z direction, which is the direction of gravity. That is, in this embodiment, the z direction is the direction of X-ray irradiation from the X-ray generator 11.
  • the installation area is larger, but it is easy to design to reduce the effects of vibration caused by the X-ray tube and to extend the overall length of the optical system, so there is a high degree of freedom in the design of the device to improve performance.
  • the device is vertical in this embodiment, it can also be horizontal.
  • the X-ray generator 11 is equipped with an X-ray source 11a, such as a Coolidge X-ray source or a rotating anode X-ray source that are widely used in medical settings. Other X-ray sources can also be used.
  • the X-ray generator 11 of this embodiment is configured to irradiate X-rays in a cone beam shape from a focal point. In other words, the X-rays are irradiated so that they spread out the further away from the X-ray generator 11.
  • the radiation source grating 12 is provided below the X-ray generator 11.
  • the radiation source grating 12 is not attached to the X-ray generator 11, but is attached to a fixed member 18a attached to a base portion 18 provided on a support 17. This is to prevent vibrations of the X-ray generator 11 caused by the rotation of the anode of the X-ray source 11a, etc., from being transmitted to the radiation source grating 12.
  • a buffer member 17a is provided between the X-ray generator 11 and the support 17 to prevent vibrations from the X-ray generator 11 from propagating to other parts of the X-ray Talbot imaging device 1, such as the support 17 (or to reduce the amount of vibration that propagates).
  • the fixed member 18a is equipped with a filter (also called an additional filter) 112 for changing the radiation quality of the X-rays that have passed through the radiation source grating 12, an irradiation field aperture 113 for narrowing the irradiation field of the irradiated X-rays, and an irradiation field lamp 114 for irradiating the subject with visible light instead of X-rays to perform alignment before irradiating the subject with X-rays.
  • a filter also called an additional filter
  • the degree of change in phase or the decrease in visibility rate varies depending on the relative angle between the lattice and the boundary between materials with different refractive indexes inside the subject or the scatterer, and when generated as a reconstructed image, the image seen according to the angle varies. Therefore, by photographing the same part of the subject H multiple times with different lattice facing angles, multiple image sets of three types of reconstructed images (absorption image, differential phase image, small angle scattering image) based on the same moire image Mo can be obtained for each angle.
  • alignment may be performed by image processing.
  • the characteristics of the subject H may be used for alignment, or a marker for alignment other than the subject H may be photographed together with the subject H and the marker may be used.
  • the imaging angle of the subject H is adjusted by the moving mechanism of the fixed unit, but a configuration may be adopted in which the X-ray source 11a, the multiple gratings 12, 14, 15 (which may be grating holders), and the X-ray detector 16 rotate as a whole around the optical axis of the X-rays, thereby enabling imaging by changing the grating facing angle between the subject H and the gratings.
  • the image processing device 2 can generate reconstructed images (absorption image, differential phase image, small angle scattering image, orientation degree image, scattering intensity image, and orientation angle image) of the subject H using the moire image Mo obtained by the X-ray Talbot imaging device 1.
  • the image processing device 2 can also perform image processing of the obtained reconstructed images.
  • the image processing device 2 is configured to include a control unit 21, an operation unit 22, a display unit 23, a communication unit 24, and a storage unit 25.
  • the image processing device 2 including the display unit 23 also functions as an image display device.
  • the control unit 21 is composed of a CPU (Central Processing Unit), a RAM (Random Access Memory), etc., and executes various processes including image processing, which will be described later, in cooperation with programs stored in the storage unit 25 .
  • the control unit 21 then functions as an image acquisition unit that acquires reconstructed images (absorption image, differential phase image, small-angle scattering image, orientation image, scattering intensity image, and orientation angle image) based on the image (moire image Mo).
  • the control unit 21 also functions as an extraction unit that extracts defects in the subject based on the reconstructed image.
  • the control unit 21 also functions as a discrimination unit that discriminates the type of void contained in the defect.
  • the control unit 21 also functions as an output unit that outputs information about the determined voids.
  • a defect is an anomaly that occurs during the manufacture of an article containing fibers and resin.
  • Defects include voids (interfiber voids, extra-interfiber voids), cracks, fiber clumps, delamination, foreign bodies, etc.
  • the interfiber voids may be voids caused by poor resin impregnation of the fibers, voids in fiber bundles or fiber clusters, or voids between fibers, fiber bundles, or fiber clusters.
  • the control unit 21 determines that voids in the vicinity of fibers are interfiber voids.
  • the interfiber voids are voids in regions where there are few fibers and where resin is the main component. Cracks, fiber aggregation, and delamination will be explained in the "Other" section.
  • the operation unit 22 is configured with a keyboard equipped with cursor keys, numeric input keys, various function keys, etc., and a pointing device such as a mouse, and outputs press signals of keys pressed on the keyboard and operation signals from the mouse as input signals to the control unit 21. It may also be configured with a touch panel integrated with the display of the display unit 23, and generate operation signals corresponding to these operations and output them to the control unit 21.
  • the display unit 23 is configured with a display such as a CRT (Cathode Ray Tube) or LCD (Liquid Crystal Display), and displays various display screens, etc., according to the display control of the control unit 21.
  • a display such as a CRT (Cathode Ray Tube) or LCD (Liquid Crystal Display), and displays various display screens, etc., according to the display control of the control unit 21.
  • the communication unit 24 has a communication interface and communicates with the X-ray Talbot imaging device 1 on the communication network and with external systems such as a PACS (Picture Archiving and Communication System) via wired or wireless communication.
  • PACS Picture Archiving and Communication System
  • the storage unit 25 is composed of a non-volatile semiconductor memory, a hard disk, etc.
  • the storage unit 25 stores the programs executed by the control unit 21, data necessary for executing the programs, information on the object to be inspected (subject H) (subject information), information on the reconstructed image, parameters for the image processing described below, etc.
  • the subject information may include the material of the subject, the fibers contained in the subject, the molding method of the subject, etc.
  • control unit 21 can detect that materials with a large density difference (here, a void and a resin or a void and a fiber) are adjacent to each other because a strong contrast is displayed between black and white in the differential phase image.
  • the control unit 21 also detects regions where fibers are predominant (fiber regions) and regions where there is no fiber and where resin is predominant (resin regions) from the scattering intensity image and the absorption image. That is, the control unit 21 determines that a region where the scattering intensity is low (black) and the absorption intensity is medium (gray), as in the elliptical frames F12 and F13, is a resin region because there are no fibers and resin is predominant.
  • the control unit 21 also determines that a region where the scattering intensity is high (white) and the absorption intensity is also high (white), as in the square frames F22 and F23, is a fiber region because fiber is predominant. The control unit 21 then determines that the areas enclosed by the elliptical frames (F11 to F13) are voids in the resin, i.e., extrafiber voids. The control unit 21 also determines that the areas enclosed by the square frames (F21 to F23) are voids in the fiber substrate, i.e., interfiber voids.
  • the control unit 21 can determine that the areas enclosed by the square frames (F21 to F23) are voids between fibers, and therefore are voids caused by insufficient impregnation of the fibers with the resin. Note that, although it may be impossible to determine the type of void depending on the photographing conditions, the type of void may be determined based on an estimate, and still useful knowledge can be obtained.
  • the position of the void may be determined using images captured by irradiating the subject H with X-rays from two or more different directions. A specific description will be given with reference to Figs. 6 and 7. In Figs. 6 and 7, the gray areas are fiber areas, the white areas are resin areas, and the circular areas are voids.
  • the voids are determined to be interfiber voids. Also, if a void exists in the resin area in either one of the images as shown in Fig. 7B, the voids are determined to be extra-fiber voids.
  • the control unit 21 performed the determination under the assumption that the constituent materials of the subject H are resin, fiber, and air (void). As shown in Figs. 8 to 10, the control unit 21 can also determine whether the material in the defective region has a higher or lower density than the surrounding materials from the transition of the signal values of the differential phase image. Therefore, when the main constituent materials are known as resin, fiber, etc., the control unit 21 can determine that if the density of the defective region is high compared to the surrounding materials such as resin or fiber, it is a high-density foreign material such as metal, and if the density is low, it is low-density air, i.e., a void. 8, the subject H contains voids and needles (foreign objects).
  • FIG. 9 is an enlarged view of a void portion (fiber resin and air) and a foreign matter portion (fiber resin and needles in this case) in a differential phase image.
  • Fig. 10 shows the transition of signal values at the points indicated by the lines in Fig. 9. From the transition of signal values, in the case of resin ⁇ air ⁇ resin, the signal value changes from a downward slope to an upward slope as shown in the above figure, and thus the control unit 21 determines that the transition is high density ⁇ low density ⁇ high density. As a result, the control unit 21 determines that the low-density portion is a void portion.
  • the control unit 21 determines that the high-density portion is a foreign matter portion. As described above, the control unit 21 can determine whether the type of defect is a foreign matter, but if information on the constituent material of the subject H is stored in the memory unit 25, it is also possible to use that information to determine what type of foreign matter the subject is (e.g., metal, etc.).
  • Image processing Next, a specific flow of image processing will be described with reference to Fig. 11. Image processing is executed by the control unit 21 in cooperation with a program stored in the storage unit 25. It is assumed that the reconstructed image and the like are stored in the storage unit 25 before the start of image processing.
  • control unit 21 acquires from the storage unit 25 a reconstructed image selected by the user using the operation unit 22 (step S1; image acquisition step).
  • control unit 21 acquires a reconstructed image such as the image shown in FIG. 12.
  • control unit 21 extracts area A (fiber area) and area B (void area) (step S2; extraction step).
  • the control unit 21 extracts area A (fiber area) and area B (B1, B2, B3; void areas) as shown in the image in FIG. 12.
  • area B (void area) is a defective area that indicates a defect.
  • the control unit 21 performs the following processing: That is, the control unit 21 extracts an area separated from the surroundings by a boundary line in the differential phase image as a large-sized void area (area B), and an area in the scattering intensity image where the signal value is higher than a threshold value as a fiber area (area A).
  • the control unit 21 When a differential phase image, a scattering intensity image, and an absorption image have been acquired, the control unit 21 performs the following processing: That is, the control unit 21 extracts an area in the differential phase image that is separated from the surroundings by a boundary line and in the absorption image that has a lower signal value than the surroundings as a large-sized void area (area B), and an area in the scattering intensity and absorption image that has a signal value higher than a threshold value as a fiber area (area A).
  • the control unit 21 When the subject H is a flat sample (the X-ray penetration distance, i.e., the thickness of the subject H is uniform), the material of the subject H is only fiber and resin, and a differential phase image and an absorption image have been acquired, the control unit 21 performs the following process. That is, the control unit 21 extracts an area in the differential phase image that is separated from the surroundings by a boundary line and in the absorption image where the signal value is lower than the surroundings as a large size void area (area B), and an area in the absorption image where the signal value is higher than the threshold value as a fiber area (area A).
  • control unit 21 classifies a portion in the absorption image where the signal value is higher than the first threshold value as a portion with high fiber density composed of fiber and resin. In addition, the control unit 21 classifies a portion in the absorption image where the signal value is equal to or lower than the first threshold value and higher than a second threshold value lower than the first threshold value as a portion with low fiber density composed of fiber and resin, or a portion without fiber and composed only of resin. In addition, the control unit 21 classifies a portion in the absorption image where the signal value is equal to or lower than the second threshold value as a portion with few fibers and resin (i.e., a portion with high possibility of being a void). Therefore, the control unit 21 can extract the above.
  • the control unit 21 extracts regions in the absorption image where the signal value is lower than the predicted absorption signal value as large size void regions (region B), and regions where the signal value is higher than the threshold value as fiber regions (region A). Note that voids that can be confirmed only in the absorption image are classified as large voids due to the discrimination ability of the absorption image.
  • the control unit 21 processes as follows. That is, the control unit 21 extracts areas in the absorption image where the signal value is lower than the threshold as large size void areas (area B), and areas in the scattering intensity where the signal value is higher than the threshold as fiber areas (area A). As above, voids that can be confirmed only in the absorption image are considered to be large voids due to the discrimination ability of the absorption image.
  • control unit 21 When a scattering intensity image and an orientation image have been acquired, and it is known that the fibers in the fiber region are strongly oriented, the control unit 21 performs the following processing. That is, the control unit 21 extracts the region in the orientation image where the signal value is higher than the threshold as the fiber region (region A), and the region in the orientation image where the signal value is lower than the threshold and the scattering intensity where the signal value is higher than the threshold as the microvoid region (region B).
  • defects can be extracted from the reconstructed image using filtering instead of signal threshold processing.
  • a bandpass filter which is a type of frequency filter
  • bandpass filtering is performed on the absorption image by dividing the spatial frequency band into several bands such as low, medium, and high frequencies, and the shape of the entire sample is extracted in the low frequency band, noise caused by the device is extracted in the high frequency band, and defect images such as voids are extracted in the medium frequency band.
  • These extracted defect images become the large size void region (region B).
  • the fiber region (region A) may be obtained from the scattering intensity image using a threshold value in the same manner as described above, or region A may be set based on the image extracted in the low frequency band using bandpass filtering.
  • the control unit 21 determines the type of voids contained in region B (void region) (step S3; determination step). That is, the control unit 21 determines that when the degree of overlap between the fiber region (region A) and the void region (region B) is higher than the determination criterion (i.e., when there is a void near the fiber), it is an interfiber void, and when the degree is lower, it is an extrafiber void.
  • 13 is an image diagram of region A (fiber region) and region B (B1, B2, B3; void regions) extracted by the control unit 21.
  • the percentage of the portion of region B (void region) that overlaps with region A (fiber region) is 40% for void B1, 100% for void B2, and 10% for void B3.
  • control unit 21 uses a percentage of 30% as a discrimination criterion and discriminates voids B1 and B2 as impregnation defects (interfiber voids) and void B3 as an extrafiber void.
  • the above criteria are merely examples and are not limiting.
  • control unit 21 outputs information about the determined voids to the display unit 23 (step S4; output step). Specifically, for example, the control unit 21 outputs the determined type of void to the display unit 23 . In addition, the control unit 21 outputs at least one piece of information regarding the number of voids, size, number of voids by size, distance between voids, maximum density area, and in-plane distribution uniformity to the display unit 23 for each type of void identified. Here, when outputting the maximum density area or the in-plane distribution uniformity, the control unit 21 divides the image into small sections, calculates the maximum density area and the in-plane distribution uniformity for each section, and outputs them to the display unit 23.
  • the control unit 21 calculates the ratio of voids to the area of the partition (density area) for each partition, and outputs the maximum density area among them as the maximum density area to the display unit 23.
  • the control unit 21 outputs the degree of variation, such as the average value (number of voids per unit area) and area ratio calculated for each section, to the display unit 23 as an index representing the in-plane uniformity.
  • the control unit 21 may output to the image display device.
  • control unit 21 can also perform image processing to determine the type of void contained in the defect by using only the small-angle scattering image. Specifically, when subject H contains fibers, if the direction of the slits is aligned with the direction of the fibers, the signal value appears strong in the reconstructed image. Taking advantage of this property, one lattice direction is set to the fiber direction and the other is set to a direction different from the fiber direction, and a small-angle scattering image is captured, a fiber region is extracted as shown in FIG. 14A, and a void region is extracted as shown in FIG. 14B.
  • a composite image is an image obtained by subjecting two or more of the above-mentioned reconstructed images (absorption image, differential phase image, small-angle scattering image, orientation image, scattering intensity image, and orientation angle image) to division, addition, or other computations (such as subtraction, multiplication, or combinations thereof).
  • the composite image may be an image obtained by performing division, addition, or other arithmetic processing on the reconstructed image and an arbitrary image.
  • the arbitrary image refers to a drawing or image obtained by a device other than the X-ray Talbot imaging device, such as a microscope image, CAD, or a photograph.
  • control unit 21 may apply the above method and output information regarding cracks, fiber aggregates, or delamination by changing the area settings (for example, setting to extract areas containing cracks or areas containing fiber aggregates).
  • a crack is a break that may or may not penetrate the outer surface or the entire thickness of a material. Delamination is also the separation of layers in a laminate due to failure in or near the adhesive bond.
  • cracks and delamination are states where air has entered the fiber-resin, similar to the voids described above.
  • cracks and delamination are defects formed by stress-induced destruction, and are characterized by their defect shape having a surface that shows a long and thin line shape according to the direction of the stress.
  • cracks and delaminations can be extracted together with voids, and by measuring the indices that represent the shape characteristics of each defect image after extraction, such as circularity, Feret diameter, and aspect ratio (ratio of width to length), setting a threshold value for the shape indices, and selecting defect images that are close to a line shape, cracks and delaminations can be extracted. Since delamination is a crack that occurs between layers of a laminate, it can be distinguished from other cracks by confirming in the reconstructed image that the position where the crack occurred in the fiber-resin laminate is between the layers and that the direction of extension is along the interlayer.
  • fiber agglomeration refers to a state in which fibers are aggregated and not defibrated during the manufacturing process of fiber-reinforced resin, or a state in which fibers that have once been dissolved and scattered are reassembled and formed into a clump.
  • fiber agglomeration is a clump (defective area) in which fibers are unintentionally gathered, unlike intentionally aggregated fiber bundles.
  • Fiber agglomeration is not limited to this, and may be a clump of fibers that is relatively denser than the surrounding area.
  • fiber agglomeration is defined based on at least one of area, circularity, Feret diameter, and aspect ratio (ratio of width to length).
  • fiber agglomeration is a fiber region in which fibers are gathered at a higher density than the surrounding area
  • additional processing for fiber agglomeration discrimination is performed on the fiber region extracted by the above-mentioned fiber region discrimination method to discriminate it.
  • the first fiber region is discriminated as a region in which both the scattering intensity and the absorption intensity are high.
  • threshold values are further set for both the scattering intensity and the absorption intensity, and the region in which fibers are gathered at a higher density on the high intensity side is separated as a fiber aggregate. At this stage, it is not possible to distinguish between high-density fiber bundles and fiber agglomerates.
  • the difference in shape between fiber agglomerates and fiber bundles is utilized, and one of the shape features of the fiber aggregates - area, circularity, Feret diameter, or aspect ratio (ratio of width to length) - is measured, and fiber agglomerates are separated and extracted based on the measurement results.
  • pre-processing is image processing for removing information that is not necessary in the output processing, and includes the following filtering and/or threshold processing.
  • the filtering process is, for example, a process using a spatial filter (median filter, averaging filter, expansion filter, contraction filter, etc.), a frequency filter, or the like.
  • the control unit 21 replaces the signal values within a range divided by N ⁇ N pixels of an absorption image or the like with either the median (median filter), average (averaging filter), maximum (expansion filter), or minimum (contraction filter) of the signal values within each range. This reduces noise in the image.
  • a median filter that can particularly reduce noise is preferable.
  • voids (air) in the fiber-reinforced resin have lower X-ray absorption than the surrounding material in the absorption image, and appear on the image as low-absorption areas. According to the sampling theorem, the size can be correctly identified in the absorption image when it is 2 x detector pixel pitch / (image magnification ratio) or more.
  • the size of voids with a diameter of 200 [ ⁇ m] or more can be determined, but voids with a diameter of less than 200 [ ⁇ m] can be detected, but the size is not known to be 150 or 50 [ ⁇ m]. Therefore, since the signal intensity of the small-angle scattering image varies depending on the size of the scatterer, the size range of the scatterer can be estimated.
  • the theoretical formula for the signal intensity of the small-angle scattering image and the size of the scatterer is shown in Equation 1 (S.K. Lynch, "Interpretation of dark-field contrast and particle size selectivity inclusion interferometers (APPLIED OPTICS.
  • the small-angle scattering signal intensity ( ⁇ d') of the voids is determined by D', and the denominator d of D' is a fixed value determined by the device and photographing conditions, so it depends on the particle diameter D.
  • Figure 15 shows the relationship between the particle size and the small-angle scattering signal intensity value ( ⁇ d) in the Talbot device. As can be seen from this figure, the size of the voids detected in the small-angle scattering image is within the range indicated by the arrow (several to about 100 [ ⁇ m]).
  • the signal intensity is relatively high, it can be estimated that there are many voids in the vicinity of several to about 30 [ ⁇ m], and if the signal intensity is low, it can be estimated that there are many voids smaller or larger than the above range.
  • factors other than the size of the voids such as the density of the voids and the thickness of the sample, may be taken into consideration. Therefore, the size range of voids in a sample can be estimated if one has the absorption image, the small-angle scattering image, and the Talbot device and imaging condition parameters used to capture the images.
  • the X-ray Talbot imaging device 1 and the image processing device 2 may be integrated into a single image processing device (image processing system).
  • an X-ray imaging system 200 includes an X-ray Talbot imaging device 3 and an image processing device 4.
  • the X-ray Talbot imaging device 3 can generate reconstructed images (absorption image, differential phase image, small angle scattering image, orientation degree image, scattering intensity image, and orientation angle image) of the subject H using a moire image Mo obtained from an imaging unit 36 described later.
  • the X-ray Talbot imaging device 3 is configured to include a control unit 31, an operation unit 32, a display unit 33, a communication unit 34, a storage unit 35, and an imaging unit 36.
  • the control unit 31 is composed of a CPU (Central Processing Unit), a RAM (Random Access Memory), etc., and executes various processes including image processing, which will be described later, in cooperation with programs stored in the storage unit 35 .
  • the control unit 31 then functions as an image acquisition unit that acquires reconstructed images (absorption image, differential phase image, small-angle scattering image, orientation image, scattering intensity image, and orientation angle image) based on the image (moire image Mo).
  • the control unit 31 also functions as an output unit that outputs information regarding voids.
  • the operation unit 32 is configured with a keyboard equipped with cursor keys, numeric input keys, various function keys, etc., and a pointing device such as a mouse, and outputs press signals of keys pressed on the keyboard and operation signals from the mouse as input signals to the control unit 31. It may also be configured with a touch panel configured integrally with the display of the display unit 33, and generate operation signals corresponding to these operations and output them to the control unit 31.
  • the display unit 33 is configured with a display such as a CRT (Cathode Ray Tube) or LCD (Liquid Crystal Display), and displays various display screens, etc., according to the display control of the control unit 21.
  • a display such as a CRT (Cathode Ray Tube) or LCD (Liquid Crystal Display), and displays various display screens, etc., according to the display control of the control unit 21.
  • the communication unit 34 includes a communication interface, and communicates with the X-ray Talbot imaging apparatus 1 on the communication network and with external systems such as a PACS (Picture Archiving and Communication System) via wired or wireless communication.
  • the communication unit 34 functions as a first transmission unit that transmits the reconstructed image to the image processing device 4 (server).
  • the communication unit 34 also functions as an information receiving unit that receives information about voids contained in the reconstructed image from the image processing device 4 (server).
  • the storage unit 35 is composed of a non-volatile semiconductor memory, a hard disk, etc., and stores the programs executed by the control unit 21, data necessary for executing the programs, information on the object to be inspected (subject H) (subject information), information on the reconstructed image, etc.
  • the subject information may include the material of the subject, the fibers contained in the subject, the molding method of the subject, etc.
  • the imaging unit 36 is similar to the X-ray detector 16 of the first embodiment.
  • the photographing unit 36 functions as a photographing unit that photographs a subject containing fibers and resin.
  • the configuration of the X-ray Talbot imaging device 3 is the same as that of the X-ray Talbot imaging device 1 of the first embodiment, except for the configuration described above.
  • the image processing device 4 (server) can perform image processing of the reconstructed image.
  • the image processing device 4 includes a control unit 41, a communication unit 42, and a storage unit 43.
  • the control unit 41 is composed of a CPU (Central Processing Unit), a RAM (Random Access Memory), etc., and executes various processes including image processing, which will be described later, in cooperation with programs stored in the storage unit 43 .
  • the control unit 41 then functions as an extraction unit that extracts defects in the subject based on the reconstructed image.
  • the control unit 41 also functions as a discrimination unit that discriminates the type of void contained in the defect.
  • the communication unit 42 includes a communication interface and communicates with the X-ray Talbot imaging apparatus 1 on the communication network and with external systems such as a PACS (Picture Archiving and Communication System) via wired or wireless communication.
  • the communication unit 42 functions as a second transmission unit that transmits information relating to the determined voids to the X-ray Talbot imaging device 3 .
  • the storage unit 43 is composed of a non-volatile semiconductor memory, a hard disk, etc., and stores the programs executed by the control unit 21, data required for executing the programs, parameters for image processing, etc.
  • the image processing device 2 generates a reconstructed image using the moire image Mo obtained by the X-ray Talbot imaging device 1, performs image processing on the reconstructed image, and outputs information regarding voids.
  • the X-ray Talbot imaging device 3 first, the X-ray Talbot imaging device 3 generates a reconstructed image using the moire image Mo, and transmits the reconstructed image to the image processing device 4 via the communication unit 34. Thereafter, the image processing device 4 performs image processing on the received reconstructed image, and transmits information regarding voids to the X-ray Talbot imaging device 3 via the communication unit 42, and finally, the X-ray Talbot imaging device 3 receives and outputs the information regarding voids. Note that the contents of each process are similar to those in the first embodiment.
  • [Third embodiment] 17 and 18 show examples of a method for obtaining three-dimensional Talbot reconstruction and three-dimensional orientation analysis images (scattering intensity, orientation angle, degree of orientation, etc.).
  • a subject H is placed in the device as shown in Fig. 17.
  • the subject H is attached to a moving/rotating mechanism 13a, and a plurality of projection images are taken at different rotation angles by rotating H as shown in Fig. 18, and a Talbot CT reconstructed image can be obtained by performing 3D reconstruction processing.
  • the Talbot CT reconstructed images are an absorption CT image obtained from a plurality of absorption projection images, a small-angle scattering CT image obtained from a plurality of small-angle scattering projection images, and a CT image obtained from a plurality of differential phase projection images.
  • a three-dimensional orientation analysis image is obtained by the following method: A subject is placed as shown in Fig. 18, and multiple projection images of the subject H are taken at different rotation angles.
  • Fig. 18 shows an example in which the lattice direction and the CT rotation axis are parallel, but other configurations are also possible in which the directions of the lattice direction and the CT rotation axis are changed, or the directions of the lattice direction and the CT rotation axis are fixed as parallel, perpendicular, or oblique, and the direction of the subject H relative to the CT rotation axis is changed.
  • a Talbot CT reconstructed image using the small-angle scattering image is obtained by performing a three-dimensional reconstruction process on each captured projection image.
  • the three-dimensional reconstruction process is performed for each captured projection image while changing the lattice direction and the direction of the CT rotation axis, and the direction of the subject H relative to the CT rotation axis, and the Talbot CT reconstructed image using each small-angle scattering image is then arithmetically processed to obtain an orientation analysis image (which may be a 3D image or a 2D image) such as scattering intensity, orientation angle, orientation degree, etc.
  • an orientation analysis image which may be a 3D image or a 2D image
  • the method of obtaining the orientation analysis image such as scattering intensity, orientation angle, orientation degree, etc. is not limited to this.
  • the image processing method is an image processing method for an image obtained by photographing a subject containing fibers and resin with an X-ray Talbot imaging device, and includes an image acquisition step S1 for acquiring a reconstructed image based on the image, an extraction step S2 for extracting defects in the subject based on the reconstructed image, a discrimination step S3 for discriminating the type of void contained in the defects, and an output step S4 for outputting information regarding the discriminated voids, thereby making it possible to output more detailed information regarding the defects in the subject containing fibers and resin.
  • interfiber voids and extra-interfiber voids in the types of voids, more detailed information about defects in subjects containing fibers and resin can be output.
  • the discrimination step S3 discriminates voids that are located near fibers as interfiber voids, thereby making it possible to output more detailed information about defects in subjects that contain fibers and resin.
  • interfiber voids are voids caused by insufficient resin impregnation of the fibers, more detailed information about defects in subjects containing fibers and resin can be output.
  • interfiber voids are voids within fiber bundles or fiber aggregates, or voids between fibers, fiber bundles, or fiber aggregates, more detailed information about defects in a subject containing fiber and resin can be output.
  • the output step S4 outputs the type of void that has been determined, making it possible to output more detailed information regarding defects in the subject that contains fibers and resin.
  • the output step S4 outputs at least one piece of information for each type of void identified, including the number of voids, their size, the number of voids by size, the distance between voids, the maximum density area, and the uniformity of distribution within the surface. This allows more detailed information about defects in the subject containing fiber and resin to be output.
  • the discrimination step S3 discriminates between cracks and fiber aggregates contained in the defect, and the output step outputs information regarding the discriminated cracks and fiber aggregates, thereby making it possible to output more detailed information regarding the defect of the subject containing fiber and resin.
  • the output step S4 outputs information about extra-interfiber voids, which are voids that do not correspond to interfiber voids, thereby making it possible to output more detailed information about defects in the subject that contains fibers and resin.
  • the X-ray Talbot imaging device 1 is an X-ray Talbot CT device, and the image is obtained by performing tomographic imaging of the subject in the depth direction using the X-ray Talbot CT device, so that more detailed information regarding defects in the subject containing fibers and resin can be output.
  • the image processing device 2 is an image processing device 2 for an image obtained by photographing a subject containing fibers and resin with an X-ray Talbot imaging device 1, and is equipped with an image acquisition unit (control unit 21) that acquires a reconstructed image based on the image, an extraction unit (control unit 21) that extracts defects in the subject based on the reconstructed image, a discrimination unit (control unit 21) that discriminates the type of void contained in the defect, and an output unit (control unit 21) that outputs information related to the discriminated void, thereby making it possible to output more detailed information related to defects in the subject containing fibers and resin.
  • the image processing system is an image processing system (X-ray imaging system 200) that includes an X-ray Talbot imaging device 1 and a server (image processing device 4).
  • the X-ray Talbot imaging device 3 includes an imaging unit 36 that images an object containing fibers and resin, an image acquisition unit (control unit 31) that acquires a reconstructed image based on the captured image, a first transmission unit (communication unit 34) that transmits the reconstructed image to the server, an information reception unit (communication unit 34) that receives information about voids contained in the reconstructed image from the server, and an output unit (control unit 31) that outputs information about the voids.
  • the server includes an extraction unit (control unit 41) that extracts defects in the object based on the reconstructed image, a discrimination unit (control unit 41) that discriminates the type of void contained in the defect, and a second transmission unit (communication unit 42) that transmits information about the discriminated voids to the X-ray Talbot imaging device, so that more detailed information about defects in the object containing fibers and resin can be output.
  • the program also causes the computer of the image processing device 2, which processes an image obtained by photographing an object containing fibers and resin with the X-ray Talbot imaging device 1, to function as an image acquisition unit (control unit 21) that acquires a reconstructed image based on the image, an extraction unit (control unit 21) that extracts defects in the object based on the reconstructed image, a discrimination unit (control unit 21) that discriminates the type of void contained in the defects, and an output unit (control unit 21) that outputs information related to the discriminated voids, thereby making it possible to output more detailed information related to defects in the object containing fibers and resin.
  • an image acquisition unit control unit 21
  • an extraction unit that extracts defects in the object based on the reconstructed image
  • a discrimination unit control unit 21
  • control unit 21 that discriminates the type of void contained in the defects
  • an output unit control unit 21
  • the image processing device 2 equipped with the display unit 23 also functions as an image display device, but the image processing device and the image display device may be separate devices.
  • the image display device may only perform display processing, and various processes and management of information such as fiber aggregation may be performed by a separate image processing device.
  • the image processing device may be a cloud, and only display processing may be performed by the image display device.
  • This disclosure can be used in image processing methods, image processing devices, image processing systems, and programs.

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Abstract

An image processing method for an image acquired by imaging an imaging subject which contains a fiber and a resin by using an X-ray Talbot imaging device, said method having: an image acquisition step S1 for acquiring a reconstructed image based on an image; an extraction step S2 for extracting a defect in the imaging subject on the basis of the reconstructed image; a determination step S3 for determining the type of void included in the defect; and an output step S4 for outputting information pertaining to the determined void.

Description

画像処理方法、画像処理装置、画像処理システム及びプログラムIMAGE PROCESSING METHOD, IMAGE PROCESSING APPARATUS, IMAGE PROCESSING SYSTEM, AND PROGRAM
　本発明は、画像処理方法、画像処理装置、画像処理システム及びプログラムに関する。 The present invention relates to an image processing method, an image processing device, an image processing system, and a program.
　昨今、自動車や航空機などの分野において、軽量化や脱炭素の世界的動きから、金属の代替として、繊維と樹脂の混合物である繊維強化樹脂を使用する動きがある。しかしながら、繊維と樹脂が充分に混合されず、繊維強化樹脂の中に欠陥が生じた場合、設計上の性能が出ないため、欠陥情報を知ることが重要である。
　特許文献１には、繊維強化樹脂に含まれる欠陥の検出方法が開示されている。 Recently, in the fields of automobiles and aircraft, there has been a trend to use fiber-reinforced resin, a mixture of fiber and resin, as an alternative to metal due to the global movement towards weight reduction and decarbonization. However, if the fiber and resin are not mixed sufficiently and defects occur in the fiber-reinforced resin, the designed performance will not be achieved, so it is important to know the defect information.
Patent Document 1 discloses a method for detecting defects in a fiber-reinforced resin.
特開２０１９－２０３１３号公報JP 2019-20313 A
　しかしながら、特許文献１に記載された欠陥の検出方法では、成形された繊維強化樹脂に欠陥がどの程度あるかを見ることを目的としているため、画像撮影で出てきた黒い筋を一律に欠陥とみなしている。
　そのため、特許文献１に記載された欠陥の検出方法では、欠陥が何に基づいているか（例えば、含浸不良、クラック、層間剥離）という情報等は検出されず、繊維強化樹脂の設計において、検出される欠陥情報としては不十分である。 However, the defect detection method described in Patent Document 1 aims to see the extent of defects in the molded fiber-reinforced resin, and therefore treats all black streaks that appear in the captured image as defects.
Therefore, the defect detection method described in Patent Document 1 does not detect information on what the defect is based on (e.g., poor impregnation, cracks, delamination), and the detected defect information is insufficient for designing fiber-reinforced resins.
　したがって、本発明の課題は、繊維と樹脂とを含有する被写体の欠陥に関する情報をより詳細に出力可能な画像処理方法、画像処理装置、画像処理システム及びプログラムを提供することを目的とする。 The present invention therefore aims to provide an image processing method, image processing device, image processing system, and program that can output more detailed information about defects in a subject that contains fibers and resin.
　上記課題を解決するため、本発明の画像処理方法は、
　繊維と樹脂とを含有する被写体をＸ線タルボ撮影装置で撮影し得られた画像の画像処理方法であって、
　前記画像に基づいた再構成画像を取得する画像取得ステップと、
　前記再構成画像に基づいて、前記被写体における欠陥を抽出する抽出ステップと、
　前記欠陥に含まれるボイドの種類を判別する判別ステップと、
　前記判別したボイドに関する情報を出力する出力ステップと、
　を有する。 In order to solve the above problems, the image processing method of the present invention comprises the steps of:
1. An image processing method for an image obtained by photographing an object containing fibers and resin with an X-ray Talbot imaging device, comprising:
an image acquisition step of acquiring a reconstructed image based on the image;
an extraction step of extracting a defect in the object based on the reconstructed image;
a determining step of determining a type of void contained in the defect;
an output step of outputting information about the determined voids;
has.
　また、本発明の画像処理装置は、
　繊維と樹脂とを含有する被写体をＸ線タルボ撮影装置で撮影し得られた画像の画像処理装置であって、
　前記画像に基づいた再構成画像を取得する画像取得部と、
　前記再構成画像に基づいて、前記被写体内の欠陥を抽出する抽出部と、
　前記欠陥に含まれるボイドの種類を判別する判別部と、
　前記判別したボイドに関する情報を出力する出力部と、
　を備える。 The image processing device of the present invention further comprises:
An image processing device for processing an image obtained by photographing an object containing fibers and resin with an X-ray Talbot imaging device, comprising:
an image acquisition unit for acquiring a reconstructed image based on the image;
an extraction unit that extracts defects in the object based on the reconstructed image;
A discrimination unit that discriminates the type of void contained in the defect;
an output unit that outputs information about the determined voids;
Equipped with.
　また、本発明の画像処理システムは、
　Ｘ線タルボ撮影装置とサーバーとを備える画像処理システムであって、
　前記Ｘ線タルボ装置は、
　繊維と樹脂とを含有する被写体を撮影する撮影部と、
前記撮影した画像に基づいた再構成画像を取得する画像取得部と、
　前記再構成画像を前記サーバーに送信する第１送信部と、
　前記再構成画像に含まれるボイドに関する情報を前記サーバーから受信する情報受信部と、
　前記ボイドに関する情報を出力する出力部と、
　を備え、
　前記サーバーは、
　前記再構成画像に基づいて、前記被写体内の欠陥を抽出する抽出部と、
　前記欠陥に含まれるボイドの種類を判別する判別部と、
　前記判別したボイドに関する情報を前記Ｘ線タルボ装置に送信する第２送信部と、
　を備える。 The image processing system of the present invention further comprises:
An image processing system including an X-ray Talbot imaging device and a server,
The X-ray Talbot device comprises:
an imaging unit that images an object containing fibers and a resin;
an image acquisition unit for acquiring a reconstructed image based on the captured image;
a first transmission unit that transmits the reconstructed image to the server;
an information receiving unit that receives information regarding voids included in the reconstructed image from the server;
an output unit that outputs information about the void;
Equipped with
The server,
an extraction unit that extracts defects in the object based on the reconstructed image;
A discrimination unit that discriminates the type of void contained in the defect;
a second transmission unit that transmits information about the determined void to the X-ray Talbot device;
Equipped with.
　また、本発明のプログラムは、
　繊維と樹脂とを含有する被写体をＸ線タルボ撮影装置で撮影し得られた画像の画像処理装置のコンピューターを、
　前記画像に基づいた再構成画像を取得する画像取得部、
　前記再構成画像に基づいて、前記被写体内の欠陥を抽出する抽出部、
　前記欠陥に含まれるボイドの種類を判別する判別部、
　前記判別したボイドに関する情報を出力する出力部、
　として機能させる。 In addition, the program of the present invention is
A computer of an image processing device for an image obtained by photographing an object containing fibers and resin with an X-ray Talbot imaging device,
an image acquisition unit for acquiring a reconstructed image based on the image;
an extraction unit that extracts defects in the object based on the reconstructed image;
A discrimination unit that discriminates the type of void contained in the defect;
an output unit that outputs information about the determined voids;
Function as.
　本発明によれば、繊維と樹脂とを含有する被写体の欠陥に関する情報をより詳細に出力できる。 The present invention makes it possible to output more detailed information about defects in subjects that contain fibers and resin.
Ｘ線タルボ撮影装置の全体像を表す概略図である。1 is a schematic diagram showing an overall view of an X-ray Talbot imaging device. タルボ干渉計の原理を説明する図である。FIG. 1 is a diagram illustrating the principle of a Talbot interferometer. 線源格子や第１格子、第２格子の概略平面図である。3 is a schematic plan view of a source grating, a first grating, and a second grating. FIG. 画像処理装置の機能的構成を示すブロック図である。FIG. 2 is a block diagram showing a functional configuration of the image processing device. 微分位相画像、散乱強度画像、吸収画像の例である。13 shows examples of a differential phase image, a scattering intensity image, and an absorption image. 被写体の立体図と撮影方向である。A three-dimensional view of the subject and the shooting direction. ２Ｄ透過像を用いたボイド検出例である。13 is an example of void detection using a 2D transmission image. 微分位相画像の例である。1 is an example of a differential phase image. 微分位相画像におけるボイド部と異物部の例である。1 shows examples of voids and foreign matter in differential phase images. ボイド部と異物部における信号値の推移の例である。13 is an example of the transition of signal values in a void portion and a foreign substance portion. 画像処理を示すフローチャートである。13 is a flowchart showing image processing. 各画像での繊維や樹脂やボイドの見え方のイメージ図である。This is an image of how fibers, resin, and voids appear in each image. 領域Ａや領域Ｂのイメージ図である。FIG. 1 is an image diagram of area A and area B. 小角散乱画像のみを使用して判別する概要図である。FIG. 13 is a schematic diagram showing discrimination using only small-angle scattering images. 小角散乱画像のみを使用して判別する概要図である。FIG. 13 is a schematic diagram showing discrimination using only small-angle scattering images. ボイドの粒子径と小角散乱信号強度の関係を示すグラフである。1 is a graph showing the relationship between void particle size and small-angle scattering signal intensity. Ｘ線撮影システムの機能的構成を示すブロック図である。FIG. 2 is a block diagram showing a functional configuration of the X-ray imaging system. ３次元タルボ撮影装置の全体像を表す概略図である。FIG. 1 is a schematic diagram showing an overall view of a three-dimensional Talbot imaging device. ３次元タルボ干渉計の原理を説明する図である。1 is a diagram illustrating the principle of a three-dimensional Talbot interferometer.
［第１実施形態］
　以下、図面を参照して本発明の実施の形態について説明する。ただし、以下に述べる実施形態には、本発明を実施するために技術的に好ましい種々の限定が付されているが、本発明の技術的範囲を以下の実施形態および図示例に限定するものではない。 [First embodiment]
Hereinafter, the embodiments of the present invention will be described with reference to the drawings. However, the embodiments described below are subject to various technically preferable limitations for carrying out the present invention, but the technical scope of the present invention is not limited to the following embodiments and illustrated examples.
　本実施形態のＸ線撮影システム１００は、図１に示すように、Ｘ線タルボ撮影装置１と、画像処理装置２と、を備える。
　Ｘ線撮影システム１００は、Ｘ線タルボ撮影装置１を用いて被写体Ｈ（検査対象物）または格子を、Ｘ線の光軸に直交する面内において回転させることにより、その相対角度を変え、複数回撮影する。そして、画像処理装置２によって、Ｘ線タルボ撮影装置１で読み取られたモアレ画像及び被写体Ｈが存在しない状態でのモアレ画像（ＢＧ：Ｂａｃｋ　Ｇｒｏｕｎｄモアレ画像と呼ぶ）に基づいて、撮影角度ごとに再構成画像を生成する。
　なお、Ｘ線撮影システム１００は、被写体Ｈが存在しない状態でのモアレ画像を少なくとも１回、被写体Ｈ撮影の事前や事後に撮影するものとする。 As shown in FIG. 1, an X-ray imaging system 100 of this embodiment includes an X-ray Talbot imaging device 1 and an image processing device 2.
The X-ray imaging system 100 rotates the subject H (inspection object) or the grid in a plane perpendicular to the optical axis of the X-rays using the X-ray Talbot imaging device 1 to change the relative angle and capture the image multiple times. Then, the image processing device 2 generates a reconstructed image for each imaging angle based on the moire image read by the X-ray Talbot imaging device 1 and a moire image in a state where the subject H does not exist (referred to as a BG: Back Ground moire image).
The X-ray imaging system 100 captures a moire image in a state in which the subject H is not present at least once before or after the imaging of the subject H.
　Ｘ線タルボ撮影装置１としては、線源格子（Ｇ０格子ともいう。）１２を備えるタルボ・ロー干渉計を用いたものが採用されている。なお、線源格子１２を備えず、第１格子（Ｇ１格子ともいう。）１４と第２格子（Ｇ２格子ともいう。）１５のみを備えるタルボ干渉計を用いたＸ線タルボ撮影装置を採用することもできる。 The X-ray Talbot imaging device 1 uses a Talbot-Lau interferometer equipped with a source grating (also called G0 grating) 12. It is also possible to use an X-ray Talbot imaging device that does not have a source grating 12 and uses a Talbot interferometer equipped only with a first grating (also called G1 grating) 14 and a second grating (also called G2 grating) 15.
　本実施形態における検査対象物は、複合材料（複合素材とも言う。）によって構成されており、例えば宇宙・航空機関係、自動車、船舶、つり竿の他、電気・電子・家電部品、パラボラアンテナ、浴槽、床材、屋根材等を始め、様々な製品等の構成部材として用いられるものである。
　このような複合材料としては、例えば炭素繊維やガラス繊維を強化繊維として用いたＣＦＲＰ（Ｃａｒｂｏｎ－Ｆｉｂｅｒ－Ｒｅｉｎｆｏｒｃｅｄ　Ｐｌａｓｔｉｃｓ：炭素繊維強化プラスチック）、ＣＦＲＴＰ（Ｃａｒｂｏｎ　Ｆｉｂｅｒ　Ｒｅｉｎｆｏｒｃｅｄ
　Ｔｈｅｒｍｏ　Ｐｌａｓｔｉｃｓ：炭素繊維強化熱可塑性プラスチック）、ＧＦＲＰ（Ｇｌａｓｓ－Ｆｉｂｅｒ－Ｒｅｉｎｆｏｒｃｅｄ　Ｐｌａｓｔｉｃｓ：ガラス繊維強化プラスチック）に代表されるＦＲＰ（Ｆｉｂｅｒ－Ｒｅｉｎｆｏｒｃｅｄ　Ｐｌａｓｔｉｃｓ：繊維強化プラスチック）や、セラミックス繊維を強化材とするＣＭＣ（Ｃｅｒａｍｉｃ　Ｍａｔｒｉｘ　Ｃｏｍｐｏｓｉｔｅｓ：セラミック基複合材料）等が知られている。
　なお、複合材料に用いられる樹脂は、例えば、汎用プラスチック、エンプラ、スーパーエンプラであるがこれらに限定されない。樹脂は、強度などの所定の特性を付加するためにマイクロサイズやナノサイズの構造を持つフィラーが添加される樹脂複合材料として用いられ、プラスチック成型加工品として使用されることが多い。フィラーには、有機材料、無機材料、磁性材料、金属材料がある。例えば、プラスチック成型加工品に強度や剛性を求められる場合には、樹脂としてＰＰＳ、ＰＯＭ、ＰＡ、ＰＣ、ＰＰなど、フィラーとしてはアラミド繊維、タルク、セルロ―ス繊維など、が用いられることがある。また、プラスチック成型加工品がプラマグである場合には、樹脂としてナイロン、フィラーとしてストロンチウムフェライト、サマリウムコバルトなど、が用いられることがある。 The object to be inspected in this embodiment is made of a composite material (also called a composite material) and is used as a component part of a variety of products, including aerospace and aircraft related products, automobiles, ships, fishing rods, as well as electrical, electronic and home appliance parts, parabolic antennas, bathtubs, flooring materials, roofing materials, etc.
Examples of such composite materials include CFRP (Carbon-Fiber-Reinforced Plastics) and CFRTP (Carbon Fiber Reinforced Plastics) that use carbon fiber or glass fiber as reinforcing fibers.
Known examples of such composite materials include FRPs (Fiber-Reinforced Plastics) such as Carbon Fiber Reinforced Thermo Plastics (CFRP), Glass Fiber Reinforced Plastics (GFRP), and Ceramic Matrix Composites (CMCs) using ceramic fibers as a reinforcing material.
The resins used in the composite materials are, for example, general-purpose plastics, engineering plastics, and super engineering plastics, but are not limited to these. Resins are used as resin composite materials to which fillers having micro- or nano-sized structures are added to impart certain properties such as strength, and are often used as plastic molded products. Fillers include organic materials, inorganic materials, magnetic materials, and metal materials. For example, when strength and rigidity are required for plastic molded products, PPS, POM, PA, PC, PP, etc. may be used as resins, and aramid fibers, talc, cellulose fibers, etc. may be used as fillers. In addition, when the plastic molded product is a plastic magnet, nylon may be used as resins, and strontium ferrite, samarium cobalt, etc. may be used as fillers.
　上記のような複合材料は、型に樹脂などを流し込む（射出成形）ことや樹脂をシート状に押し出すこと等で成型品として製造される。そして、被写体Ｈは、成型品そのものであったり、成型品から切り出されたサンプルであったりする。なお、被写体Ｈは、成型品に限定されない。 The above-mentioned composite materials are manufactured as molded products by pouring resin into a mold (injection molding) or by extruding resin into a sheet. The subject H may be the molded product itself or a sample cut out from the molded product. Note that the subject H is not limited to molded products.
［Ｘ線タルボ撮影装置について］
　図１は、本実施形態に係るＸ線タルボ撮影装置１の全体像を表す概略図である。本実施形態に係るＸ線タルボ撮影装置１は、図１に示すように、Ｘ線発生装置１１と、線源格子１２と、被写体台１３と、第１格子１４と、第２格子１５と、Ｘ線検出器１６と、支柱１７と、基台部１８と、を備えている。 [About the X-ray Talbot Imaging Device]
1 is a schematic diagram showing an overall image of an X-ray Talbot imaging device 1 according to this embodiment. As shown in FIG. 1, the X-ray Talbot imaging device 1 according to this embodiment includes an X-ray generator 11, a source grating 12, a subject table 13, a first grating 14, a second grating 15, an X-ray detector 16, a support 17, and a base unit 18.
　このようなＸ線タルボ撮影装置１によれば、被写体台１３に対して所定位置にある被写体Ｈのモアレ画像を縞走査法の原理に基づく方法で撮影したり、モアレ画像を、フーリエ変換法を用いて解析したりすることで、少なくとも３種類の画像を再構成することができる（再構成画像という）。
　すなわち、ＢＧモアレ縞画像とモアレ縞画像の平均成分の差を画像化した吸収画像（通常のＸ線の吸収画像と同じ）と、ＢＧモアレ縞画像とモアレ縞画像の位相の差を画像化した微分位相画像と、ＢＧモアレ縞画像とモアレ縞画像のＶｉｓｉｂｉｌｉｔｙ（鮮明度）の比であるＶｉｓｉｂｉｌｉｔｙ率を画像化した小角散乱画像の３種類の画像である。
　なお、上記のような再構成画像は、被写体Ｈの厚み方向の情報が圧縮された２次元画像であることとなる。 With such an X-ray Talbot imaging device 1, at least three types of images can be reconstructed (referred to as reconstructed images) by capturing a moire image of the subject H at a predetermined position relative to the subject table 13 using a method based on the principles of the fringe scanning method and analyzing the moire image using the Fourier transform method.
That is, there are three types of images: an absorption image (same as a normal X-ray absorption image) which visualizes the difference in average components between the BG moiré fringe image and the moiré fringe image; a differential phase image which visualizes the phase difference between the BG moiré fringe image and the moiré fringe image; and a small-angle scattering image which visualizes the visibility rate, which is the ratio of the visibility of the BG moiré fringe image and the moiré fringe image.
It should be noted that the above-described reconstructed image is a two-dimensional image in which information about the subject H in the thickness direction is compressed.
　なお、縞走査法とは、複数の格子のうちのひとつを格子のスリット周期の１／Ｍ（Ｍは正の整数、吸収画像はＭ＞２、微分位相画像と小角散乱画像はＭ＞３）ずつ、スリット周期方向に移動させてＭ回撮影したモアレ画像を用いて再構成を行い、高精細の再構成画像を得る方法である。 The fringe scanning method is a method in which one of multiple gratings is moved in the direction of the slit period by 1/M (M is a positive integer, M>2 for absorption images, M>3 for differential phase images and small-angle scattering images) of the grating, and then reconstructed using the moiré images captured M times to obtain a high-resolution reconstructed image.
　また、フーリエ変換法とは、被写体が存在する状態で、Ｘ線タルボ撮影装置でモアレ画像を１枚撮影し、画像処理において、そのモアレ画像をフーリエ変換する等して吸収画像、微分位相画像、小角散乱画像を再構成して生成する方法である。 The Fourier transform method is a method in which, in the presence of a subject, a single moiré image is captured using an X-ray Talbot imaging device, and then in image processing, the moiré image is subjected to a Fourier transform or other process to reconstruct and generate an absorption image, differential phase image, and small-angle scattering image.
　次に、タルボ干渉計やタルボ・ロー干渉計に共通する原理について、図２を用いて説明する。 Next, the principle common to Talbot interferometers and Talbot-Lau interferometers will be explained using Figure 2.
　なお、図２では、タルボ干渉計の場合が示されているが、タルボ・ロー干渉計の場合も
基本的に同様に説明される。また、図２におけるｚ方向が図１のＸ線タルボ撮影装置１における鉛直方向（ｚ方向）に対応し、図２におけるｘ、ｙ方向が図１のＸ線タルボ撮影装置１における水平方向（前後、左右方向）に対応する。 Although Fig. 2 shows the case of a Talbot interferometer, the case of a Talbot-Lau interferometer can be basically described in the same manner. The z direction in Fig. 2 corresponds to the vertical direction (z direction) in the X-ray Talbot imaging device 1 in Fig. 1, and the x and y directions in Fig. 2 correspond to the horizontal directions (front-back and left-right directions) in the X-ray Talbot imaging device 1 in Fig. 1.
　また、図３に示すように、第１格子１４や第２格子１５には（タルボ・ロー干渉計の場合は線源格子１２にも）、Ｘ線の照射方向であるｚ方向と直交するｘ方向に、所定の周期ｄで複数のスリットＳが平行に配列されて形成されている。
　なお、線源格子１２、第１格子１４、第２格子１５の周期は、同一の周期に限定されない。 As shown in FIG. 3 , the first grating 14 and the second grating 15 (and also the source grating 12 in the case of a Talbot-Lau interferometer) have a plurality of slits S arranged in parallel with each other at a predetermined period d in the x direction perpendicular to the z direction, which is the irradiation direction of the X-rays.
The periods of the source grating 12, the first grating 14, and the second grating 15 are not limited to being the same.
　図２に示すように、Ｘ線源１１ａ（Ｘ線発生装置１１）から照射されたＸ線（タルボ・ロー干渉計の場合はＸ線源１１ａから照射されたＸ線が線源格子１２（図２では図示省略）で多光源化されたＸ線）が第１格子１４を透過する。そして、透過したＸ線がｚ方向に一定の間隔で像を結ぶ。この像を自己像（格子像等ともいう。）といい、このように自己像がｚ方向に一定の間隔をおいて形成される現象をタルボ効果という。 As shown in Figure 2, X-rays irradiated from X-ray source 11a (X-ray generator 11) (in the case of a Talbot-Lau interferometer, the X-rays irradiated from X-ray source 11a are converted into multiple light sources by source grating 12 (not shown in Figure 2)) pass through first grating 14. The transmitted X-rays then form images at regular intervals in the z direction. These images are called self-images (also called grating images, etc.), and the phenomenon in which self-images are formed at regular intervals in the z direction is called the Talbot effect.
　すなわち、タルボ効果とは、図２に示すように一定の周期ｄでスリットＳが設けられた第１格子１４を可干渉性（コヒーレント）の光が透過すると、上記のように光の進行方向に一定の間隔でその自己像を結ぶ現象をいう。 In other words, the Talbot effect is a phenomenon in which, when coherent light passes through the first grating 14, which has slits S at a constant period d as shown in Figure 2, it forms self-images at constant intervals in the direction of light travel, as described above.
　そして、図２に示すように、第１格子１４の自己像が像を結ぶ位置に、第１格子１４の自己像と略同じ周期のスリットＳが設けられた第２格子１５を配置する。その際、第２格子１５のスリットＳの延在方向（すなわち図２ではｘ軸方向）が、第１格子１４のスリットＳの延在方向に対して略平行になるように配置すると、第２格子１５上でモアレ画像Ｍｏが得られる。 Then, as shown in FIG. 2, a second grating 15 having slits S with approximately the same period as the self-image of the first grating 14 is placed at the position where the self-image of the first grating 14 forms an image. At this time, if the extension direction of the slits S of the second grating 15 (i.e., the x-axis direction in FIG. 2) is placed approximately parallel to the extension direction of the slits S of the first grating 14, a moiré image Mo is obtained on the second grating 15.
　なお、図２では、モアレ画像Ｍｏを第２格子１５上に記載するとモアレ縞とスリットＳとが混在する状態になって分かりにくくなるため、モアレ画像Ｍｏを第２格子１５から離して記載している。しかし、実際には第２格子１５上およびその下流側でモアレ画像Ｍｏが形成される。そして、このモアレ画像Ｍｏが、第２格子１５の直下に配置されるＸ線検出器１６で撮影される。 In FIG. 2, the moire image Mo is drawn away from the second grating 15 because if the moire image Mo were drawn on the second grating 15, the moire fringes and slits S would be mixed together and would be difficult to understand. However, in reality, the moire image Mo is formed on the second grating 15 and downstream of it. This moire image Mo is then captured by the X-ray detector 16, which is placed directly below the second grating 15.
　また、図２に示すように、Ｘ線源１１ａ（Ｘ線発生装置１１）と第１格子１４との間に（すなわち図１の被写体台１３上に）被写体Ｈが存在することにより、Ｘ線の位相のずれや、Ｘ線の散乱が起こる。Ｘ線の位相のずれによりモアレ画像Ｍｏのモアレ縞が被写体の辺縁を境界に乱れ、また、Ｘ線の散乱により、被写体の辺縁に限定されず、散乱を受けた部分のビジビリティ率が低下する。一方、図示を省略するが、Ｘ線源１１ａ（Ｘ線発生装置１１）と第１格子１４との間に被写体Ｈが存在しなければ、被写体Ｈの影響を受けていないモアレ縞画像、つまりＢＧモアレ画像が現れる。以上がタルボ干渉計やタルボ・ロー干渉計の原理である。
　なお、第１格子１４は被写体Ｈの手前（Ｘ線発生装置１１側）に配置されていてもよい。 As shown in FIG. 2, the presence of the subject H between the X-ray source 11a (X-ray generating device 11) and the first grating 14 (i.e., on the subject table 13 in FIG. 1) causes a phase shift of the X-rays and scattering of the X-rays. The phase shift of the X-rays causes the moire fringes of the moire image Mo to become distorted at the boundary of the subject's edge, and the scattering of the X-rays reduces the visibility rate of the scattered portion, not limited to the edge of the subject. On the other hand, although not shown, if the subject H does not exist between the X-ray source 11a (X-ray generating device 11) and the first grating 14, a moire fringe image not influenced by the subject H, that is, a BG moire image, appears. The above is the principle of the Talbot interferometer and the Talbot-Lau interferometer.
The first grating 14 may be disposed in front of the subject H (on the X-ray generating device 11 side).
　この原理に基づいて、本実施形態に係るＸ線タルボ撮影装置１においても、例えば図１に示すように、第２のカバーユニット１３０内で、第１格子１４の自己像が像を結ぶ位置に第２格子１５が配置されるようになっている。また、第２格子１５とＸ線検出器１６とを離すとモアレ画像Ｍｏ（図２参照）がぼやけるため、本実施形態では、Ｘ線検出器１６は第２格子１５の直下に配置されるようになっている。 Based on this principle, in the X-ray Talbot imaging device 1 according to this embodiment, for example as shown in FIG. 1, the second grating 15 is arranged in the second cover unit 130 at a position where the self-image of the first grating 14 forms an image. Furthermore, since the moiré image Mo (see FIG. 2) becomes blurred when the second grating 15 and the X-ray detector 16 are separated, in this embodiment, the X-ray detector 16 is arranged directly below the second grating 15.
　なお、第２のカバーユニット１３０は、人や物が第１格子１４や第２格子１５、Ｘ線検出器１６等にぶつかったり触れたりしないようにして、Ｘ線検出器１６等を防護するために設けられている。 The second cover unit 130 is provided to protect the X-ray detector 16, etc. by preventing people or objects from colliding with or touching the first grating 14, second grating 15, X-ray detector 16, etc.
　図示を省略するが、Ｘ線検出器１６は、照射されたＸ線に応じて電気信号を生成する変換素子が二次元状（マトリクス状）に配置され、変換素子により生成された電気信号を画像信号として読み取るように構成されている。そして、本実施形態では、Ｘ線検出器１６は、第２格子１５上に形成されるＸ線の像である上記のモアレ画像Ｍｏを変換素子ごとの画像信号として撮影するようになっている。 Although not shown in the figure, the X-ray detector 16 is configured such that conversion elements that generate electrical signals in response to irradiated X-rays are arranged in a two-dimensional array (matrix), and the electrical signals generated by the conversion elements are read as image signals. In this embodiment, the X-ray detector 16 captures the moiré image Mo, which is an image of the X-rays formed on the second grating 15, as an image signal for each conversion element.
　そして、本実施形態では、Ｘ線タルボ撮影装置１は、いわゆる縞走査法を用いてモアレ画像Ｍｏを複数枚撮影するようになっている。すなわち、本実施形態に係るＸ線タルボ撮影装置１では、第１格子１４と第２格子１５との相対位置を図１～図３におけるｘ軸方向（すなわちスリットＳの延在方向（ｙ軸方向）に直交する方向）にずらしながらモアレ画像Ｍｏを複数枚撮影する。なお、別の実施形態として線源格子１２を動かしてもよい。 In this embodiment, the X-ray Talbot imaging device 1 captures multiple moiré images Mo using a so-called fringe scanning method. That is, in the X-ray Talbot imaging device 1 according to this embodiment, multiple moiré images Mo are captured while shifting the relative positions of the first grating 14 and the second grating 15 in the x-axis direction in Figures 1 to 3 (i.e., the direction perpendicular to the extension direction (y-axis direction) of the slit S). In another embodiment, the source grating 12 may be moved.
　そして、Ｘ線タルボ撮影装置１から複数枚分のモアレ画像Ｍｏの画像信号を受信した画像処理装置２における画像処理で、複数枚のモアレ画像Ｍｏに基づいて、吸収画像や、微分位相画像や、小角散乱画像等を再構成するようになっている。 Then, the image processing device 2 receives image signals of multiple moiré images Mo from the X-ray Talbot imaging device 1, and performs image processing to reconstruct an absorption image, a differential phase image, a small-angle scattering image, etc. based on the multiple moiré images Mo.
　そのため、本実施形態に係るＸ線タルボ撮影装置１で、縞走査法によりモアレ画像Ｍｏを複数枚撮影するために、第１格子１４をｘ軸方向に所定量ずつ移動させるための図示しない移動装置等が設けられている。なお、第１格子１４を移動させる代わりに第２格子１５を移動させたり、或いは両方とも移動させたりするように構成することも可能である。また、別の実施形態として線源格子１２を動かしてもよい。 For this reason, in the X-ray Talbot imaging device 1 according to this embodiment, in order to capture multiple moiré images Mo by the fringe scanning method, a moving device (not shown) is provided for moving the first grating 14 in the x-axis direction by a predetermined amount. Note that it is also possible to configure the device so that the second grating 15 is moved instead of the first grating 14, or so that both are moved. In another embodiment, the source grating 12 may be moved.
　また、Ｘ線タルボ撮影装置１で、第１格子１４と第２格子１５との相対位置を固定したままモアレ画像Ｍｏを１枚だけ撮影する。そして、画像処理装置における画像処理で、このモアレ画像Ｍｏをフーリエ変換法等を用いて解析する等して吸収画像、微分位相画像、小角散乱画像を再構成するように構成することも可能である。 Also, the X-ray Talbot imaging device 1 captures only one moire image Mo while keeping the relative positions of the first grating 14 and the second grating 15 fixed. Then, in image processing in the image processing device, this moire image Mo can be analyzed using a Fourier transform method or the like to reconstruct an absorption image, a differential phase image, and a small-angle scattering image.
　そして、この方法を用いる場合には、Ｘ線タルボ撮影装置１に必ずしも上記の移動装置等を設ける必要はない。なお、本発明は、このような移動装置が設けられていないＸ線タルボ撮影装置にも適用される。 When using this method, it is not necessary to provide the above-mentioned moving device etc. in the X-ray Talbot imaging device 1. Note that the present invention is also applicable to X-ray Talbot imaging devices that are not provided with such a moving device.
　なお、上記の３種類の再構成画像を再合成する等してさらに多くの種類の画像を生成することもできる。例えば、複数（３以上の）の格子対向角で撮影された小角散乱画像を用い、各画像の位置合わせを行ったうえで、画素ごとに、正弦波でフィッティングを行い、フィッティングパラメータを抽出する。正弦波のグラフは、横軸をサンプルと格子の相対角度とし、縦軸をある画素の小角散乱信号値とするグラフである。フィッティングパラメータとして、正弦波の振幅、平均、位相が得られる。画素ごとの振幅値を表す画像を配向度画像、画素ごとの平均値を示す画像を散乱強度画像、画素ごとの位相を示す画像を配向角度画像と呼ぶ。なお、フィッティングの方法は正弦波に限定されない。
　以降では、再構成画像を再合成することで生成された配向解析画像（配向度画像、散乱強度画像、配向角度画像）も含めて再構成画像とする。 It is also possible to generate many more types of images by recombining the above three types of reconstructed images. For example, small-angle scattering images taken at multiple (three or more) lattice facing angles are used, and after aligning each image, fitting is performed with a sine wave for each pixel to extract fitting parameters. A sine wave graph is a graph in which the horizontal axis represents the relative angle between the sample and the lattice, and the vertical axis represents the small-angle scattering signal value of a certain pixel. The amplitude, average, and phase of the sine wave are obtained as fitting parameters. An image showing the amplitude value for each pixel is called an orientation degree image, an image showing the average value for each pixel is called a scattering intensity image, and an image showing the phase for each pixel is called an orientation angle image. It is to be noted that the fitting method is not limited to a sine wave.
Hereinafter, the term "reconstructed image" will also refer to orientation analysis images (orientation degree image, scattering intensity image, and orientation angle image) generated by recombining the reconstructed images.
　本実施形態に係るＸ線タルボ撮影装置１における他の部分の構成について説明する。本実施形態では、いわゆる縦型であり、Ｘ線発生装置１１、線源格子１２、被写体台１３、第１格子１４、第２格子１５、Ｘ線検出器１６が、この順序に重力方向であるｚ方向に配置されている。すなわち、本実施形態では、ｚ方向が、Ｘ線発生装置１１からのＸ線の照射方向ということになる。本実施形態のように縦型の装置とすることにより、置面積を省スペース化でき既存の実験室や工場等に設置し易い。また、横型の装置の場合には、設置面積は広くなるが、X線管球起因の振動の影響低減用の設計や光学系の全長を伸ばすことが容易であるため性能改善の装置設計の自由度が高くなる。なお、本実施形態では縦型としているが、横型とすることもできる。 The configuration of other parts of the X-ray Talbot imaging device 1 according to this embodiment will be described. In this embodiment, the device is a so-called vertical type, and the X-ray generator 11, the radiation source grating 12, the subject table 13, the first grating 14, the second grating 15, and the X-ray detector 16 are arranged in this order in the z direction, which is the direction of gravity. That is, in this embodiment, the z direction is the direction of X-ray irradiation from the X-ray generator 11. By using a vertical type device as in this embodiment, the installation area can be saved and it is easy to install in existing laboratories, factories, etc. In addition, in the case of a horizontal type device, the installation area is larger, but it is easy to design to reduce the effects of vibration caused by the X-ray tube and to extend the overall length of the optical system, so there is a high degree of freedom in the design of the device to improve performance. Although the device is vertical in this embodiment, it can also be horizontal.
　Ｘ線発生装置１１は、Ｘ線源１１ａとして、例えば医療現場で広く一般に用いられているクーリッジＸ線源や回転陽極Ｘ線源等を備えている。また、それ以外のＸ線源を用いることも可能である。本実施形態のＸ線発生装置１１は、焦点からＸ線をコーンビーム状に照射するようになっている。すなわち、Ｘ線発生装置１１から離れるほどＸ線が広がるように照射される。 The X-ray generator 11 is equipped with an X-ray source 11a, such as a Coolidge X-ray source or a rotating anode X-ray source that are widely used in medical settings. Other X-ray sources can also be used. The X-ray generator 11 of this embodiment is configured to irradiate X-rays in a cone beam shape from a focal point. In other words, the X-rays are irradiated so that they spread out the further away from the X-ray generator 11.
　そして、本実施形態では、Ｘ線発生装置１１の下方に線源格子１２が設けられている。本実施形態では、線源格子１２は、Ｘ線発生装置１１には取り付けられず、支柱１７に設けられた基台部１８に取り付けられた固定部材１８ａに取り付けられている。これは、Ｘ線源１１ａの陽極の回転等により生じるＸ線発生装置１１の振動が線源格子１２に伝わらないようにするためである。 In this embodiment, the radiation source grating 12 is provided below the X-ray generator 11. In this embodiment, the radiation source grating 12 is not attached to the X-ray generator 11, but is attached to a fixed member 18a attached to a base portion 18 provided on a support 17. This is to prevent vibrations of the X-ray generator 11 caused by the rotation of the anode of the X-ray source 11a, etc., from being transmitted to the radiation source grating 12.
　なお、本実施形態では、Ｘ線発生装置１１の振動が支柱１７等のＸ線タルボ撮影装置１の他の部分に伝播しないようにするために（或いは伝播する振動をより小さくするために）、Ｘ線発生装置１１と支柱１７との間に緩衝部材１７ａが設けられている。 In this embodiment, a buffer member 17a is provided between the X-ray generator 11 and the support 17 to prevent vibrations from the X-ray generator 11 from propagating to other parts of the X-ray Talbot imaging device 1, such as the support 17 (or to reduce the amount of vibration that propagates).
　本実施形態では、上記の固定部材１８ａには、線源格子１２のほか、線源格子１２を透過したＸ線の線質を変えるためのろ過フィルタ（付加フィルタともいう。）１１２や、照射されるＸ線の照射野を絞るための照射野絞り１１３、Ｘ線を照射する前にＸ線の代わりに可視光を被写体に照射して位置合わせを行うための照射野ランプ１１４等が取り付けられている。 In this embodiment, in addition to the radiation source grating 12, the fixed member 18a is equipped with a filter (also called an additional filter) 112 for changing the radiation quality of the X-rays that have passed through the radiation source grating 12, an irradiation field aperture 113 for narrowing the irradiation field of the irradiated X-rays, and an irradiation field lamp 114 for irradiating the subject with visible light instead of X-rays to perform alignment before irradiating the subject with X-rays.
　なお、線源格子１２とろ過フィルタ１１２と照射野絞り１１３とは、必ずしもこの順番に設けられる必要はない。また、本実施形態では、線源格子１２等の周囲には、それらを保護するための第１のカバーユニット１２０が配置されている。 Note that the radiation source grating 12, the filtration filter 112, and the irradiation field aperture 113 do not necessarily have to be arranged in this order. In addition, in this embodiment, a first cover unit 120 is arranged around the radiation source grating 12 and other components to protect them.
　被写体台１３は、被写体Ｈを載置するための台である。被写体台１３は、Ｘ線発生装置１１から照射されるＸ線に対して被写体Ｈの位置を固定する固定ユニット（図示せず。）が設けられている。固定ユニットは、被写体Ｈを所定の位置で固定可能とする固定部と、当該固定部をＸＹ軸（２次元方向）＋Θ軸（３次元方向）に回転可能とする移動機構と、を有する。このような固定ユニットを用いることで、Ｘ線タルボ撮影装置１によって、被写体Ｈの同一部位を、撮影角度や格子対向角度（格子対向角）を変えた状態で正確に複数回撮影することができる。なお、被写体Ｈは必ずしも固定されている必要はなく、例えば、板材やダンベル試験片など、固定せずとも被写体台１３上で移動することがない被写体Ｈであれば、固定せず撮影可能である。また、移動機構は平行移動可能とする機構であってもよい。
　ここで、撮影角度とは、Ｘ線タルボ撮影装置１に対する被写体Ｈの位置を示す角度であり、具体的には、被写体台１３の後述する基準位置Ｐからの回転角度である。また、格子対向角とは、撮影された画像（もしくは、撮影後表示された画像）の方向と格子（マルチスリット１２、第１格子１４、第２格子１５）の方向との関係（角度）である。 The subject table 13 is a table on which the subject H is placed. The subject table 13 is provided with a fixing unit (not shown) that fixes the position of the subject H with respect to the X-rays irradiated from the X-ray generator 11. The fixing unit has a fixing part that can fix the subject H at a predetermined position, and a moving mechanism that can rotate the fixing part about the XY axis (two-dimensional direction) + Θ axis (three-dimensional direction). By using such a fixing unit, the same part of the subject H can be accurately photographed multiple times by the X-ray Talbot imaging device 1 while changing the shooting angle and the lattice facing angle (lattice facing angle). Note that the subject H does not necessarily need to be fixed, and if the subject H is, for example, a plate material or a dumbbell test piece that does not move on the subject table 13 even without fixing, it can be photographed without fixing. In addition, the moving mechanism may be a mechanism that allows translation.
Here, the imaging angle is an angle indicating the position of the subject H relative to the X-ray Talbot imaging device 1, and specifically, a rotation angle from a reference position P of the subject table 13, which will be described later. Also, the grating facing angle is a relationship (angle) between the direction of a captured image (or an image displayed after imaging) and the direction of the gratings (multi-slit 12, first grating 14, second grating 15).
　なお、格子と、被写体内部の屈折率が異なる材料同士の境界部、あるいは散乱体との相対角度に応じて、位相の変化量あるいはビジビリティ率の低下の度合いが異なり、再構成画像として生成された際に、当該角度に応じて見える像が異なるものとなる。したがって、被写体Ｈの同一部位を、格子対向角を変えて複数回撮影することによって、同一のモアレ画像Ｍｏを基にした３種類(吸収画像、微分位相画像、小角散乱画像)の再構成画像の画像セットを角度ごとに複数取得することができる。ここで、取得された格子対向角ごとの画像における被写体Ｈの同一部位を合わせるため、画像処理にて位置合わせをしてもよい。また、位置合わせにおいては、被写体Ｈの特徴を用いてもよいし、被写体Ｈとは別の位置合わせ用のマーカーを被写体Ｈと一緒に撮影し、そのマーカーを利用して実施してもよい。
　また、本実施形態では、被写体Ｈの撮影角度の調整を、固定ユニットの移動機構で行うものとしたが、Ｘ線源１１ａ、複数の格子１２，１４，１５（格子保持部でもよい。）及びＸ線検出器１６が、Ｘ線の光軸を回転軸とし、全体として回転することで、被写体Ｈと格子の格子対向角度を変えて撮影できるような構成を採用してもよい。 In addition, the degree of change in phase or the decrease in visibility rate varies depending on the relative angle between the lattice and the boundary between materials with different refractive indexes inside the subject or the scatterer, and when generated as a reconstructed image, the image seen according to the angle varies. Therefore, by photographing the same part of the subject H multiple times with different lattice facing angles, multiple image sets of three types of reconstructed images (absorption image, differential phase image, small angle scattering image) based on the same moire image Mo can be obtained for each angle. Here, in order to match the same part of the subject H in the images obtained for each lattice facing angle, alignment may be performed by image processing. In addition, the characteristics of the subject H may be used for alignment, or a marker for alignment other than the subject H may be photographed together with the subject H and the marker may be used.
In addition, in this embodiment, the imaging angle of the subject H is adjusted by the moving mechanism of the fixed unit, but a configuration may be adopted in which the X-ray source 11a, the multiple gratings 12, 14, 15 (which may be grating holders), and the X-ray detector 16 rotate as a whole around the optical axis of the X-rays, thereby enabling imaging by changing the grating facing angle between the subject H and the gratings.
［画像処理装置について］
　画像処理装置２は、Ｘ線タルボ撮影装置１により得られたモアレ画像Ｍｏを用いて、被写体Ｈの再構成画像（吸収画像、微分位相画像、小角散乱画像、配向度画像、散乱強度画像、配向角度画像）を生成できる。また、画像処理装置２は、得られた再構成画像の画像処理を行うことができる。このような画像処理装置２は、図４に示すように、制御部２１、操作部２２、表示部２３、通信部２４、記憶部２５を備えて構成されている。
　なお、表示部２３を備える画像処理装置２は、画像表示装置としても機能する。 [Image Processing Device]
The image processing device 2 can generate reconstructed images (absorption image, differential phase image, small angle scattering image, orientation degree image, scattering intensity image, and orientation angle image) of the subject H using the moire image Mo obtained by the X-ray Talbot imaging device 1. The image processing device 2 can also perform image processing of the obtained reconstructed images. As shown in FIG. 4, the image processing device 2 is configured to include a control unit 21, an operation unit 22, a display unit 23, a communication unit 24, and a storage unit 25.
The image processing device 2 including the display unit 23 also functions as an image display device.
　制御部２１は、ＣＰＵ（Ｃｅｎｔｒａｌ　Ｐｒｏｃｅｓｓｉｎｇ　Ｕｎｉｔ）やＲＡＭ（Ｒａｎｄｏｍ　Ａｃｃｅｓｓ　Ｍｅｍｏｒｙ）等から構成され、記憶部２５に記憶されているプログラムとの協働により、後述する画像処理を始めとする各種処理を実行する。
　そして、制御部２１は、画像（モアレ画像Ｍｏ）に基づいた再構成画像（吸収画像、微分位相画像、小角散乱画像、配向度画像、散乱強度画像、配向角度画像）を取得する画像取得部として機能する。
　また、制御部２１は、再構成画像に基づいて、被写体内の欠陥を抽出する抽出部として機能する。
　また、制御部２１は、欠陥に含まれるボイドの種類を判別する判別部として機能する。
　また、制御部２１は、判別したボイドに関する情報を出力する出力部として機能する。
　欠陥とは、繊維と樹脂とを含有する物品の製造上で生じた異常部位のことである。
　欠陥には、ボイド（繊維間ボイド、繊維間外ボイド）や、クラック、繊維凝集、層間剥離、異物などが挙げられる。
　ここで、繊維間ボイドとは、繊維に対する樹脂の含浸不良によるボイドであったり、繊維束内または繊維凝集内のボイド、あるいは繊維間、繊維束間、または繊維凝集間のボイドであったりする。また、後述する画像処理では、制御部２１は、繊維の近傍にあるボイドを繊維間ボイドとして判別している。ここで、近傍については、後述する画像処理の説明内で説明する。
　また、繊維間外ボイドとは、繊維が少なく樹脂が主体の領域におけるボイドである。
　なお、クラックや繊維凝集や層間剥離については、その他欄で説明する。 The control unit 21 is composed of a CPU (Central Processing Unit), a RAM (Random Access Memory), etc., and executes various processes including image processing, which will be described later, in cooperation with programs stored in the storage unit 25 .
The control unit 21 then functions as an image acquisition unit that acquires reconstructed images (absorption image, differential phase image, small-angle scattering image, orientation image, scattering intensity image, and orientation angle image) based on the image (moire image Mo).
The control unit 21 also functions as an extraction unit that extracts defects in the subject based on the reconstructed image.
The control unit 21 also functions as a discrimination unit that discriminates the type of void contained in the defect.
The control unit 21 also functions as an output unit that outputs information about the determined voids.
A defect is an anomaly that occurs during the manufacture of an article containing fibers and resin.
Defects include voids (interfiber voids, extra-interfiber voids), cracks, fiber clumps, delamination, foreign bodies, etc.
Here, the interfiber voids may be voids caused by poor resin impregnation of the fibers, voids in fiber bundles or fiber clusters, or voids between fibers, fiber bundles, or fiber clusters. In the image processing described below, the control unit 21 determines that voids in the vicinity of fibers are interfiber voids. Here, the vicinity will be described in the description of the image processing described below.
The interfiber voids are voids in regions where there are few fibers and where resin is the main component.
Cracks, fiber aggregation, and delamination will be explained in the "Other" section.
　操作部２２は、カーソルキー、数字入力キー、及び各種機能キー等を備えたキーボードと、マウス等のポインティングデバイスを備えて構成され、キーボードで押下操作されたキーの押下信号とマウスによる操作信号とを、入力信号として制御部２１に出力する。表示部２３のディスプレイと一体に構成されたタッチパネルを備え、これらの操作に応じた操作信号を生成して制御部２１に出力する構成としてもよい。 The operation unit 22 is configured with a keyboard equipped with cursor keys, numeric input keys, various function keys, etc., and a pointing device such as a mouse, and outputs press signals of keys pressed on the keyboard and operation signals from the mouse as input signals to the control unit 21. It may also be configured with a touch panel integrated with the display of the display unit 23, and generate operation signals corresponding to these operations and output them to the control unit 21.
　表示部２３は、例えば、ＣＲＴ（Ｃａｔｈｏｄｅ　Ｒａｙ　Ｔｕｂｅ）やＬＣＤ（Ｌｉｑｕｉｄ　Ｃｒｙｓｔａｌ　Ｄｉｓｐｌａｙ）等のディスプレイを備えて構成されており、制御部２１の表示制御に従って、各種表示画面等を表示する。 The display unit 23 is configured with a display such as a CRT (Cathode Ray Tube) or LCD (Liquid Crystal Display), and displays various display screens, etc., according to the display control of the control unit 21.
　通信部２４は、通信インターフェイスを備え、通信ネットワーク上にあるＸ線タルボ撮影装置１や、ＰＡＣＳ（Ｐｉｃｔｕｒｅ　Ａｒｃｈｉｖｉｎｇ　ａｎｄ　Ｃｏｍｍｕｎｉｃａｔｉｏｎ　Ｓｙｓｔｅｍ）等の外部システムと有線又は無線により通信する。 The communication unit 24 has a communication interface and communicates with the X-ray Talbot imaging device 1 on the communication network and with external systems such as a PACS (Picture Archiving and Communication System) via wired or wireless communication.
　記憶部２５は、不揮発性の半導体メモリーやハードディスク等により構成されている。記憶部２５は、制御部２１により実行されるプログラムやプログラムの実行に必要なデータ、検査対象物（被写体Ｈ）の情報（被写体情報）、再構成画像の情報、後述する画像処理におけるパラメータ等を記憶している。例えば、被写体情報は、被写体の材質、被写体に含まれる繊維、被写体の成型方法等が挙げられる。 The storage unit 25 is composed of a non-volatile semiconductor memory, a hard disk, etc. The storage unit 25 stores the programs executed by the control unit 21, data necessary for executing the programs, information on the object to be inspected (subject H) (subject information), information on the reconstructed image, parameters for the image processing described below, etc. For example, the subject information may include the material of the subject, the fibers contained in the subject, the molding method of the subject, etc.
（画像処理の概要）
　図５～図１０を用いて、被写体に含まれる欠陥を抽出し、欠陥に含まれるボイドの種類を判別する画像処理の概要を説明する。図５に示すように、制御部２１は、被写体Ｈの同一箇所を撮影した微分位相画像、散乱強度画像、吸収画像を取得しているものとする。なお、図５に示す被写体Ｈの構成物質は樹脂、繊維、空気（ボイド）であるとする。
　制御部２１は、微分位相画像における楕円枠Ｆ１１や四角枠Ｆ２１の箇所から、被写体Ｈに構造物があることを検出する。つまり、制御部２１は、微分位相画像において、白と黒でコントラストが強く表示されていることから、密度差大の物質（ここでは、ボイドと樹脂またはボイドと繊維）が隣接していることを検出できる。
　また、制御部２１は、散乱強度画像及び吸収画像から、繊維が主の領域（繊維領域）や繊維は無く樹脂が主の領域（樹脂領域）を検出する。つまり、制御部２１は、楕円枠Ｆ１２及び楕円枠Ｆ１３のように、散乱強度は低く(黒)、吸収強度中くらい(灰)の場合は、繊維は無く樹脂が主であるから、樹脂領域と判別する。また、制御部２１は、四角枠Ｆ２２及び四角枠Ｆ２３のように、散乱強度は高く(白)、吸収強度も高い(白)場合は、繊維が主であるから、繊維領域と判別する。
　そして、制御部２１は、楕円枠（Ｆ１１～Ｆ１３）の箇所を樹脂中の空隙、つまり、繊維間外ボイドであると判別する。また、制御部２１は、四角枠（Ｆ２１～Ｆ２３）の箇所を繊維基材中の空隙、つまり、繊維間ボイドであると判別する。したがって、制御部２１は、四角枠（Ｆ２１～Ｆ２３）の箇所を、繊維間のボイドであるから、繊維に対する樹脂の含浸不良によるボイドと判別できる。なお、撮影条件によってはボイドの種類を確定できない場合も考えられるが、ボイドの種類の判別にあたっては、推定に基づき判別を行ってもよく、それでも十分に役に立つ知見を得ることができる。
　なお、２Ｄ透過像を使用する場合では、被写体Ｈに対して異なる２つ以上の方向からＸ線を照射して撮影した画像を使いボイドの位置を判別してもよい。具体的に、図６及び図７を用いて説明する。図６及び図７において、灰色箇所を繊維領域、白色箇所を樹脂領域、円形箇所をボイドとする。図６に示す被写体を正面方向と側面方向から撮影した２種類の画像について、図７Ａのように正面と側面どちらも繊維領域とボイドが重なっている場合には繊維間ボイドであると判別する。また、図７Ｂのようにどちらか片方の画像でボイドが樹脂領域に存在する場合は繊維間外ボイドと判別する。 (Image processing overview)
5 to 10, an overview of image processing for extracting defects contained in a subject and determining the type of void contained in the defects will be described. As shown in Fig. 5, it is assumed that the control unit 21 acquires a differential phase image, a scattering intensity image, and an absorption image captured at the same location of the subject H. It is assumed that the constituent materials of the subject H shown in Fig. 5 are resin, fiber, and air (void).
The control unit 21 detects the presence of a structure in the subject H from the location of the elliptical frame F11 or the rectangular frame F21 in the differential phase image. In other words, the control unit 21 can detect that materials with a large density difference (here, a void and a resin or a void and a fiber) are adjacent to each other because a strong contrast is displayed between black and white in the differential phase image.
The control unit 21 also detects regions where fibers are predominant (fiber regions) and regions where there is no fiber and where resin is predominant (resin regions) from the scattering intensity image and the absorption image. That is, the control unit 21 determines that a region where the scattering intensity is low (black) and the absorption intensity is medium (gray), as in the elliptical frames F12 and F13, is a resin region because there are no fibers and resin is predominant. The control unit 21 also determines that a region where the scattering intensity is high (white) and the absorption intensity is also high (white), as in the square frames F22 and F23, is a fiber region because fiber is predominant.
The control unit 21 then determines that the areas enclosed by the elliptical frames (F11 to F13) are voids in the resin, i.e., extrafiber voids. The control unit 21 also determines that the areas enclosed by the square frames (F21 to F23) are voids in the fiber substrate, i.e., interfiber voids. Therefore, the control unit 21 can determine that the areas enclosed by the square frames (F21 to F23) are voids between fibers, and therefore are voids caused by insufficient impregnation of the fibers with the resin. Note that, although it may be impossible to determine the type of void depending on the photographing conditions, the type of void may be determined based on an estimate, and still useful knowledge can be obtained.
When using a 2D transmission image, the position of the void may be determined using images captured by irradiating the subject H with X-rays from two or more different directions. A specific description will be given with reference to Figs. 6 and 7. In Figs. 6 and 7, the gray areas are fiber areas, the white areas are resin areas, and the circular areas are voids. For two types of images captured from the front and side of the subject shown in Fig. 6, if the fiber areas and voids overlap in both the front and side views as shown in Fig. 7A, the voids are determined to be interfiber voids. Also, if a void exists in the resin area in either one of the images as shown in Fig. 7B, the voids are determined to be extra-fiber voids.
　図５では、被写体Ｈの構成物質は樹脂、繊維、空気（ボイド）であるという前提のもと、制御部２１は判別を行った。図８～図１０のように、制御部２１は、微分位相画像の信号値の推移から、欠陥領域の物質が周囲の物質よりも密度が高いか低いかを判別する事も可能である。したがって、制御部２１は、主な構成物質が樹脂、繊維などの様に既知の場合には、周囲の物質である樹脂や繊維に対して欠陥領域の密度が高い場合は金属等の高密度の異物、密度が低い場合には低密度の空気つまりボイドであると判別できる。
　図８の微分位相画像に示すように、被写体Ｈには、ボイドと針（異物）が含まれている。なお、微分位相画像の画像スキャン方向（画像信号の微分を取る方向）は、左から右（矢印で示す方向）である。
　図９は、微分位相画像における、ボイド部（繊維樹脂と空気）と異物部（繊維樹脂とここでは針）の拡大図である。
　図１０は、図９の線で示された箇所の信号値の推移を示す。制御部２１は、信号値の推移から、樹脂→空気→樹脂の場合は、上図のように信号値が右下がりから右上がりになることから、高密度→低密度→高密度であると判別する。これにより、制御部２１、低密度部位をボイド部であると判別する。また、制御部２１は、信号値の推移から、樹脂→異物→樹脂の場合は、上図のように信号値が右上がりから右下がりになることから、低密度→高密度→低密度であると判別する。これにより、制御部２１は、高密度部位を異物部であると判別する。
　なお、上記のように、制御部２１は、欠陥の種類が異物であるか判別できるが、記憶部２５に被写体Ｈの構成物質の情報が記憶されている場合、その情報を用いることで、異物が何であるか（例えば、金属など）判別することも可能である。 In Fig. 5, the control unit 21 performed the determination under the assumption that the constituent materials of the subject H are resin, fiber, and air (void). As shown in Figs. 8 to 10, the control unit 21 can also determine whether the material in the defective region has a higher or lower density than the surrounding materials from the transition of the signal values of the differential phase image. Therefore, when the main constituent materials are known as resin, fiber, etc., the control unit 21 can determine that if the density of the defective region is high compared to the surrounding materials such as resin or fiber, it is a high-density foreign material such as metal, and if the density is low, it is low-density air, i.e., a void.
8, the subject H contains voids and needles (foreign objects). The image scanning direction of the differential phase image (the direction in which the image signal is differentiated) is from left to right (the direction indicated by the arrow).
FIG. 9 is an enlarged view of a void portion (fiber resin and air) and a foreign matter portion (fiber resin and needles in this case) in a differential phase image.
Fig. 10 shows the transition of signal values at the points indicated by the lines in Fig. 9. From the transition of signal values, in the case of resin → air → resin, the signal value changes from a downward slope to an upward slope as shown in the above figure, and thus the control unit 21 determines that the transition is high density → low density → high density. As a result, the control unit 21 determines that the low-density portion is a void portion. Also, from the transition of signal values, in the case of resin → foreign matter → resin, the signal value changes from an upward slope to a downward slope as shown in the above figure, and thus the transition is low density → high density → low density. As a result, the control unit 21 determines that the high-density portion is a foreign matter portion.
As described above, the control unit 21 can determine whether the type of defect is a foreign matter, but if information on the constituent material of the subject H is stored in the memory unit 25, it is also possible to use that information to determine what type of foreign matter the subject is (e.g., metal, etc.).
（画像処理）
　次に、具体的な画像処理のフローを、図１１を用いて説明する。画像処理は、制御部２１と、記憶部２５に記憶されているプログラムとの協働により実行される。
　なお、画像処理開始前に、記憶部２５に、再構成画像等は記憶されているものとする。 (Image processing)
Next, a specific flow of image processing will be described with reference to Fig. 11. Image processing is executed by the control unit 21 in cooperation with a program stored in the storage unit 25.
It is assumed that the reconstructed image and the like are stored in the storage unit 25 before the start of image processing.
　まず、制御部２１は、記憶部２５から、ユーザーにより操作部２２を用いて選択された再構成画像を取得する（ステップＳ１；画像取得ステップ）。ここでは、制御部２１は、図１２に示すイメージのような再構成画像を取得するものとする。 First, the control unit 21 acquires from the storage unit 25 a reconstructed image selected by the user using the operation unit 22 (step S1; image acquisition step). Here, the control unit 21 acquires a reconstructed image such as the image shown in FIG. 12.
　次に、制御部２１は、領域Ａ（繊維領域）や領域Ｂ（ボイド領域）を抽出する（ステップＳ２；抽出ステップ）。ここでは、制御部２１は、図１２に示すイメージのように領域Ａ（繊維領域）や領域Ｂ（Ｂ１、Ｂ２、Ｂ３；ボイド領域）を抽出するものとする。なお、領域Ｂ（ボイド領域）は、欠陥を示す欠陥箇所である。 Next, the control unit 21 extracts area A (fiber area) and area B (void area) (step S2; extraction step). Here, the control unit 21 extracts area A (fiber area) and area B (B1, B2, B3; void areas) as shown in the image in FIG. 12. Note that area B (void area) is a defective area that indicates a defect.
　具体的には、ステップＳ１で取得された画像の種類によって、以下のように抽出される情報が異なる。
　微分位相画像と散乱強度画像が取得されている場合、制御部２１は、以下のように処理する。すなわち、制御部２１は、微分位相画像で周囲と境界線で区切られた領域を大サイズボイド領域（領域Ｂ）、散乱強度画像で信号値が閾値よりも高い領域を繊維領域（領域Ａ）として各々抽出する。
　微分位相画像と散乱強度画像と吸収画像が取得されている場合、制御部２１は、以下のように処理する。すなわち、制御部２１は、微分位相画像で周囲と境界線で区切られており且つ吸収画像で信号値が周囲よりも低い領域を大サイズボイド領域（領域Ｂ）、散乱強度と吸収画像で信号値が閾値よりも高い領域を繊維領域（領域Ａ）として各々抽出する。 Specifically, the information extracted varies depending on the type of image acquired in step S1, as follows.
When a differential phase image and a scattering intensity image have been acquired, the control unit 21 performs the following processing: That is, the control unit 21 extracts an area separated from the surroundings by a boundary line in the differential phase image as a large-sized void area (area B), and an area in the scattering intensity image where the signal value is higher than a threshold value as a fiber area (area A).
When a differential phase image, a scattering intensity image, and an absorption image have been acquired, the control unit 21 performs the following processing: That is, the control unit 21 extracts an area in the differential phase image that is separated from the surroundings by a boundary line and in the absorption image that has a lower signal value than the surroundings as a large-sized void area (area B), and an area in the scattering intensity and absorption image that has a signal value higher than a threshold value as a fiber area (area A).
　被写体Ｈが平らなサンプル（Ｘ線透過距離、つまり、被写体Ｈの厚さが均一）であり、且つ、被写体Ｈの材料が繊維と樹脂のみであり、且つ、微分位相画像と吸収画像が取得されている場合、制御部２１は、以下のように処理する。すなわち、制御部２１は、微分位相画像で周囲と境界線で区切られており且つ吸収画像で信号値が周囲よりも低い領域を大サイズボイド領域（領域Ｂ）、吸収画像で信号値が閾値よりも高い領域を繊維領域（領域Ａ）として各々抽出する。なお、この場合では、制御部２１は、吸収画像において、信号値が第１閾値よりも高い箇所を繊維と樹脂で構成された繊維密度が高い箇所と分類する。また、制御部２１は、吸収画像において、信号値が第１閾値以下で且つ第１閾値よりも低い第２閾値よりも高い箇所を繊維と樹脂で構成された繊維密度が低い箇所または繊維が無く樹脂のみで構成された箇所と分類する。また、制御部２１は、吸収画像において、信号値が第２閾値以下の箇所を繊維も樹脂も少ない箇所（つまり、ボイドの可能性が高い箇所）と分類する。このため、制御部２１は、上記のように抽出できる。 When the subject H is a flat sample (the X-ray penetration distance, i.e., the thickness of the subject H is uniform), the material of the subject H is only fiber and resin, and a differential phase image and an absorption image have been acquired, the control unit 21 performs the following process. That is, the control unit 21 extracts an area in the differential phase image that is separated from the surroundings by a boundary line and in the absorption image where the signal value is lower than the surroundings as a large size void area (area B), and an area in the absorption image where the signal value is higher than the threshold value as a fiber area (area A). In this case, the control unit 21 classifies a portion in the absorption image where the signal value is higher than the first threshold value as a portion with high fiber density composed of fiber and resin. In addition, the control unit 21 classifies a portion in the absorption image where the signal value is equal to or lower than the first threshold value and higher than a second threshold value lower than the first threshold value as a portion with low fiber density composed of fiber and resin, or a portion without fiber and composed only of resin. In addition, the control unit 21 classifies a portion in the absorption image where the signal value is equal to or lower than the second threshold value as a portion with few fibers and resin (i.e., a portion with high possibility of being a void). Therefore, the control unit 21 can extract the above.
　被写体Ｈの繊維領域において繊維と樹脂が均一な混合比で混ざっている場合には、被写体Ｈの厚さと吸収画像における信号値が、ある一定の関係性を持つ。つまり、被写体Ｈの厚さから予測される吸収信号値よりも信号が低い領域はボイドの可能性が高い、と分類できる。よって、制御部２１は、吸収画像で信号値が予想される吸収信号値よりも低い領域を大サイズボイド領域（領域Ｂ）、信号値が閾値よりも高い領域を繊維領域（領域Ａ）と抽出する。なお、吸収画像のみで確認できるボイドは、吸収画像の判別能から、大ボイドとなる。 When fibers and resin are mixed in a uniform ratio in the fiber region of subject H, there is a certain relationship between the thickness of subject H and the signal value in the absorption image. In other words, regions where the signal is lower than the absorption signal value predicted from the thickness of subject H can be classified as likely to be voids. Therefore, the control unit 21 extracts regions in the absorption image where the signal value is lower than the predicted absorption signal value as large size void regions (region B), and regions where the signal value is higher than the threshold value as fiber regions (region A). Note that voids that can be confirmed only in the absorption image are classified as large voids due to the discrimination ability of the absorption image.
　吸収画像と散乱強度画像が取得されている場合、制御部２１は、以下のように処理する。すなわち、制御部２１は、吸収画像で信号値が閾値よりも低い領域を大サイズボイド領域（領域Ｂ）、散乱強度で信号値が閾値よりも高い領域を繊維領域（領域Ａ）として抽出する。上記同様、吸収画像のみで確認できるボイドは、吸収画像の判別能から、大ボイドとなる。 When an absorption image and a scattering intensity image have been acquired, the control unit 21 processes as follows. That is, the control unit 21 extracts areas in the absorption image where the signal value is lower than the threshold as large size void areas (area B), and areas in the scattering intensity where the signal value is higher than the threshold as fiber areas (area A). As above, voids that can be confirmed only in the absorption image are considered to be large voids due to the discrimination ability of the absorption image.
　散乱強度画像と配向度画像が取得されている場合であり、且つ繊維領域の繊維が強く配向している事が分かっている場合、制御部２１は、以下のように処理する。すなわち、制御部２１は、配向度画像で信号値が閾値よりも高い領域を繊維領域（領域Ａ）とし、配向度画像で信号値が閾値よりも低く、散乱強度で信号値が閾値よりも高い領域を微小ボイド領域（領域Ｂ）として抽出する。 When a scattering intensity image and an orientation image have been acquired, and it is known that the fibers in the fiber region are strongly oriented, the control unit 21 performs the following processing. That is, the control unit 21 extracts the region in the orientation image where the signal value is higher than the threshold as the fiber region (region A), and the region in the orientation image where the signal value is lower than the threshold and the scattering intensity where the signal value is higher than the threshold as the microvoid region (region B).
　また、再構成画像からの欠陥抽出は信号閾値処理では無くフィルタ処理を使って行う事も可能である。
　例えば、周波数フィルタの１種であるバンドパスフィルタを使えば画像に含まれる空間周波数の中のある特定帯域の周波数のみ、つまり特定サイズの構造物像のみを抽出した画像を得る事が出来る。
　吸収画像と散乱強度画像が取得されている場合、吸収画像に対して空間周波数帯域を低、中、高周波数など幾つかに分けたバンドパスフィルタ処理を行うと、低周波数帯域ではサンプル全体の形状、高周波数帯域では装置起因のノイズ、中周波数帯域ではボイド等の欠陥像が抽出される。この抽出された欠陥像が大サイズボイド領域（領域Ｂ）となる。繊維領域（領域Ａ）は散乱強度画像から閾値を使い前述と同様に得ても良いし、バンドパスフィルタ処理を使い低周波数帯域で抽出された像を基に領域Ａを設定しても良い。 Furthermore, defects can be extracted from the reconstructed image using filtering instead of signal threshold processing.
For example, by using a bandpass filter, which is a type of frequency filter, it is possible to obtain an image that extracts only a specific frequency band from the spatial frequencies contained in the image, that is, only structural images of a specific size.
When an absorption image and a scattering intensity image are acquired, bandpass filtering is performed on the absorption image by dividing the spatial frequency band into several bands such as low, medium, and high frequencies, and the shape of the entire sample is extracted in the low frequency band, noise caused by the device is extracted in the high frequency band, and defect images such as voids are extracted in the medium frequency band. These extracted defect images become the large size void region (region B). The fiber region (region A) may be obtained from the scattering intensity image using a threshold value in the same manner as described above, or region A may be set based on the image extracted in the low frequency band using bandpass filtering.
　次に、制御部２１は、領域Ｂ（ボイド領域）に含まれるボイドの種類を判別する（ステップＳ３；判別ステップ）。つまり、制御部２１は、繊維領域（領域Ａ）とボイド領域（領域Ｂ）の重なり度合いが判別基準よりも高い場合（つまり、繊維の近傍にボイドがある場合）を繊維間ボイド、低い場合を繊維間外ボイドとして判別する。
　図１３は、制御部２１が抽出した領域Ａ（繊維領域）や領域Ｂ（Ｂ１、Ｂ２、Ｂ３；ボイド領域）のイメージ図である。ここで、領域Ｂ（ボイド領域）のうち、領域Ａ（繊維領域）と重なっている部分の割合を示すと、ボイドＢ１では４０％、ボイドＢ２では１００％、ボイドＢ３では１０％となる。そして、ここでは、制御部２１は、割合３０％を判別基準として、ボイドＢ１及びボイドＢ２は含浸不良（繊維間ボイド）、ボイドＢ３は繊維間外ボイドと判別する。
　なお、上記基準は、一例であり、上記基準に限定されない。 Next, the control unit 21 determines the type of voids contained in region B (void region) (step S3; determination step). That is, the control unit 21 determines that when the degree of overlap between the fiber region (region A) and the void region (region B) is higher than the determination criterion (i.e., when there is a void near the fiber), it is an interfiber void, and when the degree is lower, it is an extrafiber void.
13 is an image diagram of region A (fiber region) and region B (B1, B2, B3; void regions) extracted by the control unit 21. Here, the percentage of the portion of region B (void region) that overlaps with region A (fiber region) is 40% for void B1, 100% for void B2, and 10% for void B3. Here, the control unit 21 uses a percentage of 30% as a discrimination criterion and discriminates voids B1 and B2 as impregnation defects (interfiber voids) and void B3 as an extrafiber void.
The above criteria are merely examples and are not limiting.
　次に、制御部２１は、判別したボイドに関する情報を、表示部２３に出力する（ステップＳ４；出力ステップ）。
　具体的には、例えば、制御部２１は、判別したボイドの種類を表示部２３に出力する。
　また、制御部２１は、ボイドの個数、サイズ、サイズごとの個数、ボイド間の距離、最大密度面積、面内分布均一性の少なくとも一つの情報を、判別したボイドの種類別に表示部２３に出力する。
　ここで、制御部２１は、最大密度面積や面内分布均一性を出力する場合は、画像を小区画に区切り、区画ごとに最大密度面積や面内分布均一性を算出し、表示部２３に出力する。
　最大密度面積を出力する場合、制御部２１は、区画ごとに区画の面積に対するボイドが占める割合（密度面積）を算出し、そのうち最大の密度面積を最大密度面積として表示部２３に出力する。
　面内分布均一性を出力する場合、制御部２１は、区画ごとに算出した平均値（単位面積あたりのボイドの個数）や面積比などの、バラツキ度合いを面内の均一さを表す指標として表示部２３に出力する。
　なお、上記では、制御部２１は、表示部２３に出力する例を示したが、これに限定されない。例えば、画像処理装置２とは別に画像表示装置がある場合、制御部２１は、画像表示装置に出力してもよい。 Next, the control unit 21 outputs information about the determined voids to the display unit 23 (step S4; output step).
Specifically, for example, the control unit 21 outputs the determined type of void to the display unit 23 .
In addition, the control unit 21 outputs at least one piece of information regarding the number of voids, size, number of voids by size, distance between voids, maximum density area, and in-plane distribution uniformity to the display unit 23 for each type of void identified.
Here, when outputting the maximum density area or the in-plane distribution uniformity, the control unit 21 divides the image into small sections, calculates the maximum density area and the in-plane distribution uniformity for each section, and outputs them to the display unit 23.
When outputting the maximum density area, the control unit 21 calculates the ratio of voids to the area of the partition (density area) for each partition, and outputs the maximum density area among them as the maximum density area to the display unit 23.
When outputting the in-plane distribution uniformity, the control unit 21 outputs the degree of variation, such as the average value (number of voids per unit area) and area ratio calculated for each section, to the display unit 23 as an index representing the in-plane uniformity.
In the above, an example in which the control unit 21 outputs to the display unit 23 has been described, but the present invention is not limited to this. For example, in a case where an image display device is provided separately from the image processing device 2, the control unit 21 may output to the image display device.
（その他）
　なお、図１４Ａ及び図１４Ｂのように、制御部２１は、小角散乱画像のみ使用し、欠陥に含まれるボイドの種類を判別する画像処理を行うことも可能である。具体的には、被写体Ｈに繊維が含有されている場合、繊維の向きの方向にスリットの方向が揃っているときに、再構成画像では、信号値が強く出るという性質を活かし、格子の方向を、一方は繊維の方向、他方は繊維の方向と異なる方向として、小角散乱画像を撮影すると、図１４Ａのように繊維領域が抽出され、図１４Ｂのようにボイド領域が抽出される。 (others)
14A and 14B, the control unit 21 can also perform image processing to determine the type of void contained in the defect by using only the small-angle scattering image. Specifically, when subject H contains fibers, if the direction of the slits is aligned with the direction of the fibers, the signal value appears strong in the reconstructed image. Taking advantage of this property, one lattice direction is set to the fiber direction and the other is set to a direction different from the fiber direction, and a small-angle scattering image is captured, a fiber region is extracted as shown in FIG. 14A, and a void region is extracted as shown in FIG. 14B.
　また、合成画像を用いて、欠陥に含まれるボイドの種類を判別する画像処理を行うことも可能である。例えば、合成画像（配向度画像の信号値と微分位相画像の信号値を合成）を用いることで、大サイズのボイドの位置を判別しやすくなる。
　なお、合成画像とは、上記した再構成画像（吸収画像、微分位相画像、小角散乱画像、配向度画像、散乱強度画像、配向角度画像）のうち、２つ以上の画像を除算、加算、その他（減算、乗算、それらの組合せ演算などの演算）の演算処理をしたものである。
　また、合成画像は、再構成画像と任意の画像を除算、加算、その他の演算処理をしたものであってもよい。任意の画像とは、顕微鏡画像やＣＡＤや写真などのＸ線タルボ撮影装置以外の装置で取得した図面や画像などを指す。 It is also possible to perform image processing using the composite image to identify the type of void contained in the defect. For example, by using a composite image (combining the signal values of the orientation image and the differential phase image), it becomes easier to identify the location of a large void.
A composite image is an image obtained by subjecting two or more of the above-mentioned reconstructed images (absorption image, differential phase image, small-angle scattering image, orientation image, scattering intensity image, and orientation angle image) to division, addition, or other computations (such as subtraction, multiplication, or combinations thereof).
The composite image may be an image obtained by performing division, addition, or other arithmetic processing on the reconstructed image and an arbitrary image. The arbitrary image refers to a drawing or image obtained by a device other than the X-ray Talbot imaging device, such as a microscope image, CAD, or a photograph.
　また、制御部２１は、上記方法を応用し、領域の設定（例えば、クラックが含まれる領域や繊維凝集が含まれる領域を抽出するように設定）を変えることで、クラックや繊維凝集や層間剥離に関する情報を出力してもよい。
　なお、クラックとは、材料の外面又はその全厚さを貫通しているか又は貫通していない割れ目である。
　また、層間剥離とは、接着剤接合の中又はその近くにおける破壊が原因の積層品における層の分離である。
　ここで、クラックや層間剥離は、前述のボイドと同様に空気が繊維樹脂内に入り込んだ状態である。但しクラックと層間剥離は応力による破壊で形成される欠陥であることから応力が掛かる方向に応じて細長い線形状を示す面を持つ欠陥形状となる事に特徴がある。したがって、前述のボイド抽出と同じ画像信号強度を基にした抽出手法を行う事でボイドと一緒にクラックや層間剥離を抽出し、抽出後の各欠陥像について形状の特徴を表す指標、例えば円形度やフェレ径、アスペクト比(幅と長さの割合)等を計測して形状指標値にある閾値を設定して線形状に近い欠陥像を選定する事でクラックや層間剥離を抽出する事が出来る。層間剥離は積層品の層間で起こるクラックであるため、繊維樹脂の積層品においてクラックが発生した位置が層間であり、延びている方向が層間に沿っている事を再構成画像にて確認する事で他のクラックと判別する事が出来る。
　また、繊維凝集とは、繊維強化樹脂の製造工程の中で凝集し解繊せず塊になった状態、または、一旦解けてバラバラになった繊維が再び集合して塊になった状態をいう。すなわち、繊維凝集は、意図的に凝集された繊維束と異なり、意図せず繊維が集まった塊（不良個所）である。繊維凝集はこれに限定されず、周囲と比べて相対的に密度が高い繊維が集まった塊であればよい。具体的には、繊維凝集は、少なくとも面積、円形度、フェレ径、アスペクト比（幅と長さの割合）の１つに基づき規定される。なお、繊維凝集は繊維が周囲よりも高密度で集まっている繊維領域であるため、前述の繊維領域判別手法で抽出された繊維領域に対して繊維凝集判別用の追加処理を行い判別する。例えば、散乱強度画像と吸収画像が得られている場合、第1繊維領域は散乱強度と吸収強度の両方が高い領域として判別される。この第1繊維領域の中で更に散乱強度と吸収強度両方について閾値を設定して高強度側をより繊維が高密度に集まっている領域を繊維集合体として分離する。この段階では高密度繊維束と繊維凝集の区別がつかないため繊維凝集と繊維束の形状に違いがある事を利用し、繊維集合体の形状特徴量として面積、円形度、フェレ径、アスペクト比（幅と長さの割合）の１つを計測して計測結果に基づき繊維凝集を分離抽出する。 In addition, the control unit 21 may apply the above method and output information regarding cracks, fiber aggregates, or delamination by changing the area settings (for example, setting to extract areas containing cracks or areas containing fiber aggregates).
A crack is a break that may or may not penetrate the outer surface or the entire thickness of a material.
Delamination is also the separation of layers in a laminate due to failure in or near the adhesive bond.
Here, cracks and delamination are states where air has entered the fiber-resin, similar to the voids described above. However, cracks and delamination are defects formed by stress-induced destruction, and are characterized by their defect shape having a surface that shows a long and thin line shape according to the direction of the stress. Therefore, by performing the same extraction method based on image signal intensity as the void extraction described above, cracks and delaminations can be extracted together with voids, and by measuring the indices that represent the shape characteristics of each defect image after extraction, such as circularity, Feret diameter, and aspect ratio (ratio of width to length), setting a threshold value for the shape indices, and selecting defect images that are close to a line shape, cracks and delaminations can be extracted. Since delamination is a crack that occurs between layers of a laminate, it can be distinguished from other cracks by confirming in the reconstructed image that the position where the crack occurred in the fiber-resin laminate is between the layers and that the direction of extension is along the interlayer.
In addition, fiber agglomeration refers to a state in which fibers are aggregated and not defibrated during the manufacturing process of fiber-reinforced resin, or a state in which fibers that have once been dissolved and scattered are reassembled and formed into a clump. In other words, fiber agglomeration is a clump (defective area) in which fibers are unintentionally gathered, unlike intentionally aggregated fiber bundles. Fiber agglomeration is not limited to this, and may be a clump of fibers that is relatively denser than the surrounding area. Specifically, fiber agglomeration is defined based on at least one of area, circularity, Feret diameter, and aspect ratio (ratio of width to length). Since fiber agglomeration is a fiber region in which fibers are gathered at a higher density than the surrounding area, additional processing for fiber agglomeration discrimination is performed on the fiber region extracted by the above-mentioned fiber region discrimination method to discriminate it. For example, when a scattering intensity image and an absorption image are obtained, the first fiber region is discriminated as a region in which both the scattering intensity and the absorption intensity are high. In this first fiber region, threshold values are further set for both the scattering intensity and the absorption intensity, and the region in which fibers are gathered at a higher density on the high intensity side is separated as a fiber aggregate. At this stage, it is not possible to distinguish between high-density fiber bundles and fiber agglomerates. Therefore, the difference in shape between fiber agglomerates and fiber bundles is utilized, and one of the shape features of the fiber aggregates - area, circularity, Feret diameter, or aspect ratio (ratio of width to length) - is measured, and fiber agglomerates are separated and extracted based on the measurement results.
　また、ステップＳ１の後に、前処理を行ってもよい。前処理とは、出力処理において不要となる情報を除去するための画像処理であり、下記のようなフィルタ処理及び／または閾値処理等を含む。
　フィルタ処理とは、例えば、空間フィルタ（メディアンフィルタ、平均化フィルタ、膨張フィルタ、収縮フィルタ、等）や周波数フィルタ等を用いた処理である。
　具体的には、制御部２１は、例えば、吸収画像等のＮ×Ｎの画素で区切られた範囲内の信号値を、各範囲内の信号値の中央値（メディアンフィルタ）、平均値（平均化フィルタ）、最大値（膨張フィルタ）、最小値（収縮フィルタ）のいずれかに置き換える。これにより、画像内のノイズが低減される。特にノイズを低減できる、メディアンフィルタが好ましい。
　また、吸収画像等に含まれる不要な情報の周波数成分が既知の場合は、周波数処理を実施し不要な情報を除去してもよい。周波数フィルタは、例えば、ローパスフィルタ、ハイパスフィルタ、バンドパスフィルタ等である。
　閾値処理とは、例えば、任意の輝度範囲を設定し、範囲外を０、範囲内を１とした二値画像を生成する処理である。
　なお、前処理は、トリミング処理を含む。ユーザーにより、操作部２２を用いて画像の範囲が指定されると、制御部２１は、画像からその範囲を切り出す。例えば、被写体Ｈの端部などの情報が不要の場合、ユーザーは不要な範囲を削除ことが可能である。 Furthermore, after step S1, pre-processing may be performed. The pre-processing is image processing for removing information that is not necessary in the output processing, and includes the following filtering and/or threshold processing.
The filtering process is, for example, a process using a spatial filter (median filter, averaging filter, expansion filter, contraction filter, etc.), a frequency filter, or the like.
Specifically, the control unit 21 replaces the signal values within a range divided by N×N pixels of an absorption image or the like with either the median (median filter), average (averaging filter), maximum (expansion filter), or minimum (contraction filter) of the signal values within each range. This reduces noise in the image. A median filter that can particularly reduce noise is preferable.
In addition, when the frequency components of unnecessary information contained in the absorption image or the like are known, the unnecessary information may be removed by performing frequency processing. The frequency filter may be, for example, a low-pass filter, a high-pass filter, or a band-pass filter.
Threshold processing is, for example, processing in which an arbitrary luminance range is set, and a binary image is generated in which values outside the range are set to 0 and values within the range are set to 1.
The pre-processing includes a trimming process. When the user specifies an area of the image using the operation unit 22, the control unit 21 cuts out that area from the image. For example, if information such as the edge of the subject H is unnecessary, the user can delete the unnecessary area.
　また、ボイドの数量、形状を計測することも可能である。
　検査対象物が繊維強化樹脂である場合、繊維強化樹脂中のボイド（空気）は、吸収画像において、Ｘ線吸収が周囲の物質より低く、低吸収領域として画像上に現れる。標本化定理より吸収像で正しくサイズが識別できるのは２×検出器画素ピッチ／（画像拡大率）以上である。例えば、画素ピッチ２００［μｍ］で拡大率２倍の場合、直径２００［μｍ］以上のボイドのサイズは分かるが、２００［μｍ］未満のボイドは検出されるがサイズは１５０か５０［μｍ］か分からない。
　そこで、小角散乱画像の信号強度は散乱体のサイズにより変わるため、散乱体のサイズ範囲を推定する事ができる。小角散乱画像の信号強度と散乱体のサイズの理論式を数１に示す（Ｓ．Ｋ．Ｌｙｎｃｈ『Ｉｎｔｅｒｐｒｅｔａｔｉｏｎ　ｏｆ　ｄａｒｋ－ｆｉｅｌｄ　ｃｏｎｔｒａｓｔ　ａｎｄ　ｐａｒｔｉｃｌｅ　ｓｉｚｅ　ｓｅｌｅｃｔｉｖｉｔｙ　ｉｎ　ｇｒａｔｉｏｎ　ｉｎｔｅｒｆｅｒｏｍｅｔｅｒｓ（ＡＰＰＬＩＥＤ　ＯＰＴＩＣＳ．　Ｖｏｌ．５０，Ｎｏ．２２，ｐ４３１０（２０１１））』）。以下では、小角散乱画像の信号強度から、ボイドのサイズ範囲を推定する例を説明する。
Figure JPOXMLDOC01-appb-M000001
 　サイズが異なるボイド集合体Ａ、Ｂを含む１枚の板状の繊維強化樹脂試料（被写体Ｈ）をタルボで撮影した場合、ボイドＡ，Ｂは同じ装置且つＸ線照射条件で画像撮影される。また、ボイド＝空気でありＡとＢは同一化合物、ボイドを取り囲む物質は繊維と樹脂の混合物でありマクロ的に見ればＡ，Ｂは同じ物質に囲まれている。この場合、理論式によればボイドの小角散乱信号強度（μｄ’）は、Ｄ’で決まりＤ’の分母ｄは装置と撮影条件で決まる固定値のため粒子径Ｄに依存する。図１５に、タルボ装置での粒径と小角散乱信号強度値（μｄ）の関係を示した。この図より分かるように、小角散乱画像で検出されているボイドのサイズは矢印の範囲内（数～約１００［μｍ］）である。更に例えば信号強度が相対的に高い場合は数～約３０［μｍ］付近のボイドが多く存在すると推定できるし、信号強度が低い場合は、前記範囲より小さい、あるいは大きいボイドが多く存在すると推定できる。なお推定にあたっては、ボイドの大きさ以外の要素として、ボイドの密度、試料の厚さなどを考慮しても良い。
　従って、吸収画像と小角散乱画像、画像撮影に使われたタルボ装置・撮影条件パラメータがあれば試料中のボイドのサイズ範囲を推定する事ができる。 It is also possible to measure the number and shape of voids.
When the object to be inspected is fiber-reinforced resin, voids (air) in the fiber-reinforced resin have lower X-ray absorption than the surrounding material in the absorption image, and appear on the image as low-absorption areas. According to the sampling theorem, the size can be correctly identified in the absorption image when it is 2 x detector pixel pitch / (image magnification ratio) or more. For example, when the pixel pitch is 200 [μm] and the magnification ratio is 2 times, the size of voids with a diameter of 200 [μm] or more can be determined, but voids with a diameter of less than 200 [μm] can be detected, but the size is not known to be 150 or 50 [μm].
Therefore, since the signal intensity of the small-angle scattering image varies depending on the size of the scatterer, the size range of the scatterer can be estimated. The theoretical formula for the signal intensity of the small-angle scattering image and the size of the scatterer is shown in Equation 1 (S.K. Lynch, "Interpretation of dark-field contrast and particle size selectivity inclusion interferometers (APPLIED OPTICS. Vol.50, No.22, p4310 (2011))"). In the following, an example of estimating the size range of a void from the signal intensity of the small-angle scattering image will be described.
Figure JPOXMLDOC01-appb-M000001
 When a sheet-shaped fiber-reinforced resin sample (subject H) containing void aggregates A and B of different sizes is photographed with a Talbot, images of the voids A and B are taken with the same device and X-ray irradiation conditions. In addition, the voids = air, A and B are the same compound, and the material surrounding the voids is a mixture of fibers and resin, so that A and B are surrounded by the same material when viewed macroscopically. In this case, according to the theoretical formula, the small-angle scattering signal intensity (μd') of the voids is determined by D', and the denominator d of D' is a fixed value determined by the device and photographing conditions, so it depends on the particle diameter D. Figure 15 shows the relationship between the particle size and the small-angle scattering signal intensity value (μd) in the Talbot device. As can be seen from this figure, the size of the voids detected in the small-angle scattering image is within the range indicated by the arrow (several to about 100 [μm]). Furthermore, for example, if the signal intensity is relatively high, it can be estimated that there are many voids in the vicinity of several to about 30 [μm], and if the signal intensity is low, it can be estimated that there are many voids smaller or larger than the above range. In addition, in the estimation, factors other than the size of the voids, such as the density of the voids and the thickness of the sample, may be taken into consideration.
Therefore, the size range of voids in a sample can be estimated if one has the absorption image, the small-angle scattering image, and the Talbot device and imaging condition parameters used to capture the images.
　また、Ｘ線タルボ撮影装置１と画像処理装置２を一体とし、一つの画像処理装置（画像処理システム）としてもよい。 In addition, the X-ray Talbot imaging device 1 and the image processing device 2 may be integrated into a single image processing device (image processing system).
［第２実施形態］
　第２実施形態のＸ線撮影システム２００は、図１６に示すように、Ｘ線タルボ撮影装置３と、画像処理装置４と、を備える。 [Second embodiment]
As shown in FIG. 16, an X-ray imaging system 200 according to the second embodiment includes an X-ray Talbot imaging device 3 and an image processing device 4.
［Ｘ線タルボ撮影装置について］
　Ｘ線タルボ撮影装置３は、後述する撮影部３６から得られたモアレ画像Ｍｏを用いて、被写体Ｈの再構成画像（吸収画像、微分位相画像、小角散乱画像、配向度画像、散乱強度画像、配向角度画像）を生成することができる。Ｘ線タルボ撮影装置３は、制御部３１、操作部３２、表示部３３、通信部３４、記憶部３５、撮影部３６を備えて構成されている。 [About the X-ray Talbot Imaging Device]
The X-ray Talbot imaging device 3 can generate reconstructed images (absorption image, differential phase image, small angle scattering image, orientation degree image, scattering intensity image, and orientation angle image) of the subject H using a moire image Mo obtained from an imaging unit 36 described later. The X-ray Talbot imaging device 3 is configured to include a control unit 31, an operation unit 32, a display unit 33, a communication unit 34, a storage unit 35, and an imaging unit 36.
　制御部３１は、ＣＰＵ（Ｃｅｎｔｒａｌ　Ｐｒｏｃｅｓｓｉｎｇ　Ｕｎｉｔ）やＲＡＭ（Ｒａｎｄｏｍ　Ａｃｃｅｓｓ　Ｍｅｍｏｒｙ）等から構成され、記憶部３５に記憶されているプログラムとの協働により、後述する画像処理を始めとする各種処理を実行する。
　そして、制御部３１は、画像（モアレ画像Ｍｏ）に基づいた再構成画像（吸収画像、微分位相画像、小角散乱画像、配向度画像、散乱強度画像、配向角度画像）を取得する画像取得部として機能する。
　また、制御部３１は、ボイドに関する情報を出力する出力部として機能する。 The control unit 31 is composed of a CPU (Central Processing Unit), a RAM (Random Access Memory), etc., and executes various processes including image processing, which will be described later, in cooperation with programs stored in the storage unit 35 .
The control unit 31 then functions as an image acquisition unit that acquires reconstructed images (absorption image, differential phase image, small-angle scattering image, orientation image, scattering intensity image, and orientation angle image) based on the image (moire image Mo).
The control unit 31 also functions as an output unit that outputs information regarding voids.
　操作部３２は、カーソルキー、数字入力キー、及び各種機能キー等を備えたキーボードと、マウス等のポインティングデバイスを備えて構成され、キーボードで押下操作されたキーの押下信号とマウスによる操作信号とを、入力信号として制御部３１に出力する。表示部３３のディスプレイと一体に構成されたタッチパネルを備え、これらの操作に応じた操作信号を生成して制御部３１に出力する構成としてもよい。 The operation unit 32 is configured with a keyboard equipped with cursor keys, numeric input keys, various function keys, etc., and a pointing device such as a mouse, and outputs press signals of keys pressed on the keyboard and operation signals from the mouse as input signals to the control unit 31. It may also be configured with a touch panel configured integrally with the display of the display unit 33, and generate operation signals corresponding to these operations and output them to the control unit 31.
　表示部３３は、例えば、ＣＲＴ（Ｃａｔｈｏｄｅ　Ｒａｙ　Ｔｕｂｅ）やＬＣＤ（Ｌｉｑｕｉｄ　Ｃｒｙｓｔａｌ　Ｄｉｓｐｌａｙ）等のディスプレイを備えて構成されており、制御部２１の表示制御に従って、各種表示画面等を表示する。 The display unit 33 is configured with a display such as a CRT (Cathode Ray Tube) or LCD (Liquid Crystal Display), and displays various display screens, etc., according to the display control of the control unit 21.
　通信部３４は、通信インターフェイスを備え、通信ネットワーク上にあるＸ線タルボ撮影装置１や、ＰＡＣＳ（Ｐｉｃｔｕｒｅ　Ａｒｃｈｉｖｉｎｇ　ａｎｄ　Ｃｏｍｍｕｎｉｃａｔｉｏｎ　Ｓｙｓｔｅｍ）等の外部システムと有線又は無線により通信する。
　そして、通信部３４は、再構成画像を画像処理装置４（サーバー）に送信する第１送信部として機能する。
　また、通信部３４は、再構成画像に含まれるボイドに関する情報を画像処理装置４（サーバー）から受信する情報受信部として機能する。 The communication unit 34 includes a communication interface, and communicates with the X-ray Talbot imaging apparatus 1 on the communication network and with external systems such as a PACS (Picture Archiving and Communication System) via wired or wireless communication.
The communication unit 34 functions as a first transmission unit that transmits the reconstructed image to the image processing device 4 (server).
The communication unit 34 also functions as an information receiving unit that receives information about voids contained in the reconstructed image from the image processing device 4 (server).
　記憶部３５は、不揮発性の半導体メモリーやハードディスク等により構成され、制御部２１により実行されるプログラムやプログラムの実行に必要なデータ、検査対象物（被写体Ｈ）の情報（被写体情報）、再構成画像の情報等を記憶している。例えば、被写体情報は、被写体の材質、被写体に含まれる繊維、被写体の成型方法等が挙げられる。 The storage unit 35 is composed of a non-volatile semiconductor memory, a hard disk, etc., and stores the programs executed by the control unit 21, data necessary for executing the programs, information on the object to be inspected (subject H) (subject information), information on the reconstructed image, etc. For example, the subject information may include the material of the subject, the fibers contained in the subject, the molding method of the subject, etc.
　撮影部３６は、第１実施形態のＸ線検出器１６と同様である。
　つまり、撮影部３６は、繊維と樹脂とを含有する被写体を撮影する撮影部として機能する。 The imaging unit 36 is similar to the X-ray detector 16 of the first embodiment.
In other words, the photographing unit 36 functions as a photographing unit that photographs a subject containing fibers and resin.
　なお、Ｘ線タルボ撮影装置３の構成のうち、以上に示す構成以外は、第１実施形態のＸ線タルボ撮影装置１と同様である。 Note that the configuration of the X-ray Talbot imaging device 3 is the same as that of the X-ray Talbot imaging device 1 of the first embodiment, except for the configuration described above.
［画像処理装置について］
　画像処理装置４（サーバー）は、再構成画像の画像処理を行うことができる。画像処理装置４は、制御部４１、通信部４２、記憶部４３を備えて構成されている。 [Image Processing Device]
The image processing device 4 (server) can perform image processing of the reconstructed image. The image processing device 4 includes a control unit 41, a communication unit 42, and a storage unit 43.
　制御部４１は、ＣＰＵ（Ｃｅｎｔｒａｌ　Ｐｒｏｃｅｓｓｉｎｇ　Ｕｎｉｔ）やＲＡＭ（Ｒａｎｄｏｍ　Ａｃｃｅｓｓ　Ｍｅｍｏｒｙ）等から構成され、記憶部４３に記憶されているプログラムとの協働により、後述する画像処理を始めとする各種処理を実行する。
　そして、制御部４１は、再構成画像に基づいて、被写体内の欠陥を抽出する抽出部として機能する。
　また、制御部４１は、欠陥に含まれるボイドの種類を判別する判別部として機能する。 The control unit 41 is composed of a CPU (Central Processing Unit), a RAM (Random Access Memory), etc., and executes various processes including image processing, which will be described later, in cooperation with programs stored in the storage unit 43 .
The control unit 41 then functions as an extraction unit that extracts defects in the subject based on the reconstructed image.
The control unit 41 also functions as a discrimination unit that discriminates the type of void contained in the defect.
　通信部４２は、通信インターフェイスを備え、通信ネットワーク上にあるＸ線タルボ撮影装置１や、ＰＡＣＳ（Ｐｉｃｔｕｒｅ　Ａｒｃｈｉｖｉｎｇ　ａｎｄ　Ｃｏｍｍｕｎｉｃａｔｉｏｎ　Ｓｙｓｔｅｍ）等の外部システムと有線又は無線により通信する。
　そして、通信部４２は、判別したボイドに関する情報をＸ線タルボ撮影装置３に送信する第２送信部として機能する。 The communication unit 42 includes a communication interface and communicates with the X-ray Talbot imaging apparatus 1 on the communication network and with external systems such as a PACS (Picture Archiving and Communication System) via wired or wireless communication.
The communication unit 42 functions as a second transmission unit that transmits information relating to the determined voids to the X-ray Talbot imaging device 3 .
　記憶部４３は、不揮発性の半導体メモリーやハードディスク等により構成され、制御部２１により実行されるプログラムやプログラムの実行に必要なデータ、画像処理におけるパラメータ等を記憶している。 The storage unit 43 is composed of a non-volatile semiconductor memory, a hard disk, etc., and stores the programs executed by the control unit 21, data required for executing the programs, parameters for image processing, etc.
（処理）
　第１実施形態では、画像処理装置２が、Ｘ線タルボ撮影装置１により得られたモアレ画像Ｍｏを用いて再構成画像を生成し、再構成画像の画像処理を行い、ボイドに関する情報を出力していた。一方、第２実施形態では、まず、Ｘ線タルボ撮影装置３がモアレ画像Ｍｏを用いて再構成画像を生成し、通信部３４を介して画像処理装置４に再構成画像を送信する。その後、画像処理装置４は、受信した再構成画像の画像処理を行い、通信部４２を介してＸ線タルボ撮影装置３にボイドに関する情報を送信し、最後に、Ｘ線タルボ撮影装置３がボイドに関する情報を受信し出力する。なお、各処理の内容は、第１実施形態と同様である。 (process)
In the first embodiment, the image processing device 2 generates a reconstructed image using the moire image Mo obtained by the X-ray Talbot imaging device 1, performs image processing on the reconstructed image, and outputs information regarding voids. On the other hand, in the second embodiment, first, the X-ray Talbot imaging device 3 generates a reconstructed image using the moire image Mo, and transmits the reconstructed image to the image processing device 4 via the communication unit 34. Thereafter, the image processing device 4 performs image processing on the received reconstructed image, and transmits information regarding voids to the X-ray Talbot imaging device 3 via the communication unit 42, and finally, the X-ray Talbot imaging device 3 receives and outputs the information regarding voids. Note that the contents of each process are similar to those in the first embodiment.
［第３実施形態］
　図１７及び図１８に、３次元タルボ再構成、３次元配向解析画像(散乱強度、配向角度、配向度など)取得法の例を示す。
　図１７の様に装置に被写体Ｈを配置する。被写体Ｈは移動・回転機構１３ａに取り付けられており図１８の様にＨを回転させて異なる回転角度で複数の投影像を撮影し、３次元再構成処理を行う事でタルボＣＴ再構成画像が取得できる。タルボＣＴ再構成画像とは、複数の吸収投影像から得られる吸収ＣＴ画像、複数の小角散乱投影像から得られる小角散乱ＣＴ画像、複数の微分位相投影像から得られるＣＴ画像である。
　一方、３次元の配向解析画像は以下の方法で取得する。図１８の様に被写体を設置し、被写体Ｈを異なる回転角度で複数の投影像を撮影する。図１８には格子方向とＣＴ回転軸の方向が平行を一例として示したが、他に格子方向とＣＴ回転軸の方向を変える構成や格子方向とＣＴ回転軸の方向は平行や直交や斜め方向等で固定とし、ＣＴ回転軸に対する被写体Ｈの方向を変える構成でも良い。
　次に、撮影された各投影像に対し、３次元再構成処理を行う事で小角散乱画像を用いたタルボＣＴ再構成画像を取得する。格子方向とＣＴ回転軸の方向やＣＴ回転軸に対する被写体Ｈの方向を変えて撮影した投影像の撮影毎に３次元再構成処理を行う事で得られた各小角散乱画像を用いたタルボＣＴ再構成画像を演算処理することで、散乱強度、配向角度、配向度などの配向解析画像（３Ｄ画像でも２Ｄ画像でも良い）を得る。ただし、散乱強度、配向角度、配向度などの配向解析画像の取得方法はこれに限らない。 [Third embodiment]
17 and 18 show examples of a method for obtaining three-dimensional Talbot reconstruction and three-dimensional orientation analysis images (scattering intensity, orientation angle, degree of orientation, etc.).
A subject H is placed in the device as shown in Fig. 17. The subject H is attached to a moving/rotating mechanism 13a, and a plurality of projection images are taken at different rotation angles by rotating H as shown in Fig. 18, and a Talbot CT reconstructed image can be obtained by performing 3D reconstruction processing. The Talbot CT reconstructed images are an absorption CT image obtained from a plurality of absorption projection images, a small-angle scattering CT image obtained from a plurality of small-angle scattering projection images, and a CT image obtained from a plurality of differential phase projection images.
On the other hand, a three-dimensional orientation analysis image is obtained by the following method: A subject is placed as shown in Fig. 18, and multiple projection images of the subject H are taken at different rotation angles. Fig. 18 shows an example in which the lattice direction and the CT rotation axis are parallel, but other configurations are also possible in which the directions of the lattice direction and the CT rotation axis are changed, or the directions of the lattice direction and the CT rotation axis are fixed as parallel, perpendicular, or oblique, and the direction of the subject H relative to the CT rotation axis is changed.
Next, a Talbot CT reconstructed image using the small-angle scattering image is obtained by performing a three-dimensional reconstruction process on each captured projection image. The three-dimensional reconstruction process is performed for each captured projection image while changing the lattice direction and the direction of the CT rotation axis, and the direction of the subject H relative to the CT rotation axis, and the Talbot CT reconstructed image using each small-angle scattering image is then arithmetically processed to obtain an orientation analysis image (which may be a 3D image or a 2D image) such as scattering intensity, orientation angle, orientation degree, etc. However, the method of obtaining the orientation analysis image such as scattering intensity, orientation angle, orientation degree, etc. is not limited to this.
（効果）
　以上説明したように、画像処理方法は、繊維と樹脂とを含有する被写体をＸ線タルボ撮影装置で撮影し得られた画像の画像処理方法であって、画像に基づいた再構成画像を取得する画像取得ステップＳ１と、再構成画像に基づいて、被写体における欠陥を抽出する抽出ステップＳ２と、欠陥に含まれるボイドの種類を判別する判別ステップＳ３と、判別したボイドに関する情報を出力する出力ステップＳ４と、を有することで、繊維と樹脂とを含有する被写体の欠陥に関する情報をより詳細に出力できる。 (effect)
As described above, the image processing method is an image processing method for an image obtained by photographing a subject containing fibers and resin with an X-ray Talbot imaging device, and includes an image acquisition step S1 for acquiring a reconstructed image based on the image, an extraction step S2 for extracting defects in the subject based on the reconstructed image, a discrimination step S3 for discriminating the type of void contained in the defects, and an output step S4 for outputting information regarding the discriminated voids, thereby making it possible to output more detailed information regarding the defects in the subject containing fibers and resin.
　また、ボイドの種類には、繊維間ボイドまたは繊維間外ボイドが含まれることで、繊維と樹脂とを含有する被写体の欠陥に関する情報をより詳細に出力できる。 In addition, by including interfiber voids and extra-interfiber voids in the types of voids, more detailed information about defects in subjects containing fibers and resin can be output.
　また、判別ステップＳ３は、欠陥のうち、繊維の近傍にあるボイドを繊維間ボイドとして判別することで、繊維と樹脂とを含有する被写体の欠陥に関する情報をより詳細に出力できる。 In addition, the discrimination step S3 discriminates voids that are located near fibers as interfiber voids, thereby making it possible to output more detailed information about defects in subjects that contain fibers and resin.
　また、繊維間ボイドは、繊維に対する樹脂の含浸不良によるボイドであることで、繊維と樹脂とを含有する被写体の欠陥に関する情報をより詳細に出力できる。 In addition, since interfiber voids are voids caused by insufficient resin impregnation of the fibers, more detailed information about defects in subjects containing fibers and resin can be output.
　また、繊維間ボイドは、繊維束内または繊維凝集内のボイド、あるいは繊維間、繊維束間、または繊維凝集間のボイドであることで、繊維と樹脂とを含有する被写体の欠陥に関する情報をより詳細に出力できる。 In addition, since the interfiber voids are voids within fiber bundles or fiber aggregates, or voids between fibers, fiber bundles, or fiber aggregates, more detailed information about defects in a subject containing fiber and resin can be output.
　また、出力ステップＳ４は、判別したボイドの種類を出力することで、繊維と樹脂とを含有する被写体の欠陥に関する情報をより詳細に出力できる。 In addition, the output step S4 outputs the type of void that has been determined, making it possible to output more detailed information regarding defects in the subject that contains fibers and resin.
　また、出力ステップＳ４は、ボイドの個数、大きさ、サイズごとの個数、ボイド間の距離、最大密度面積、面内分布均一性の少なくとも一つの情報を、判別したボイドの種類別に出力する。これにより、繊維と樹脂とを含有する被写体の欠陥に関する情報をより詳細に出力できる。 In addition, the output step S4 outputs at least one piece of information for each type of void identified, including the number of voids, their size, the number of voids by size, the distance between voids, the maximum density area, and the uniformity of distribution within the surface. This allows more detailed information about defects in the subject containing fiber and resin to be output.
　また、判別ステップＳ３は、欠陥に含まれるクラックと繊維凝集を判別し、出力ステップは、判別したクラックと繊維凝集に関する情報を出力することで、繊維と樹脂とを含有する被写体の欠陥に関する情報をより詳細に出力できる。 In addition, the discrimination step S3 discriminates between cracks and fiber aggregates contained in the defect, and the output step outputs information regarding the discriminated cracks and fiber aggregates, thereby making it possible to output more detailed information regarding the defect of the subject containing fiber and resin.
　また、出力ステップＳ４は、繊維間ボイドに該当しないボイドである繊維間外ボイドに関する情報を出力することで、繊維と樹脂とを含有する被写体の欠陥に関する情報をより詳細に出力できる。 In addition, the output step S4 outputs information about extra-interfiber voids, which are voids that do not correspond to interfiber voids, thereby making it possible to output more detailed information about defects in the subject that contains fibers and resin.
　また、Ｘ線タルボ撮影装置１は、Ｘ線タルボＣＴ装置であり、画像は、Ｘ線タルボＣＴ装置で被写体の奥行方向を断層撮影することで得られる画像であることで、繊維と樹脂とを含有する被写体の欠陥に関する情報をより詳細に出力できる。 The X-ray Talbot imaging device 1 is an X-ray Talbot CT device, and the image is obtained by performing tomographic imaging of the subject in the depth direction using the X-ray Talbot CT device, so that more detailed information regarding defects in the subject containing fibers and resin can be output.
　また、画像処理装置２は、繊維と樹脂とを含有する被写体をＸ線タルボ撮影装置１で撮影し得られた画像の画像処理装置２であって、画像に基づいた再構成画像を取得する画像取得部（制御部２１）と、再構成画像に基づいて、被写体内の欠陥を抽出する抽出部（制御部２１）と、欠陥に含まれるボイドの種類を判別する判別部（制御部２１）と、判別したボイドに関する情報を出力する出力部（制御部２１）と、を備えることで、繊維と樹脂とを含有する被写体の欠陥に関する情報をより詳細に出力できる。 The image processing device 2 is an image processing device 2 for an image obtained by photographing a subject containing fibers and resin with an X-ray Talbot imaging device 1, and is equipped with an image acquisition unit (control unit 21) that acquires a reconstructed image based on the image, an extraction unit (control unit 21) that extracts defects in the subject based on the reconstructed image, a discrimination unit (control unit 21) that discriminates the type of void contained in the defect, and an output unit (control unit 21) that outputs information related to the discriminated void, thereby making it possible to output more detailed information related to defects in the subject containing fibers and resin.
　また、画像処理システム（Ｘ線撮影システム２００）は、Ｘ線タルボ撮影装置１とサーバー（画像処理装置４）とを備える画像処理システム（Ｘ線撮影システム２００）であって、Ｘ線タルボ撮影装置３は、繊維と樹脂とを含有する被写体を撮影する撮影部３６と、撮影した画像に基づいた再構成画像を取得する画像取得部（制御部３１）と、再構成画像をサーバーに送信する第１送信部（通信部３４）と、再構成画像に含まれるボイドに関する情報をサーバーから受信する情報受信部（通信部３４）と、ボイドに関する情報を出力する出力部（制御部３１）と、を備え、サーバー（画像処理装置４）は、再構成画像に基づいて、被写体内の欠陥を抽出する抽出部（制御部４１）と、欠陥に含まれるボイドの種類を判別する判別部（制御部４１）と、判別したボイドに関する情報をＸ線タルボ撮影装置に送信する第２送信部（通信部４２）と、を備えることで、繊維と樹脂とを含有する被写体の欠陥に関する情報をより詳細に出力できる。 The image processing system (X-ray imaging system 200) is an image processing system (X-ray imaging system 200) that includes an X-ray Talbot imaging device 1 and a server (image processing device 4). The X-ray Talbot imaging device 3 includes an imaging unit 36 that images an object containing fibers and resin, an image acquisition unit (control unit 31) that acquires a reconstructed image based on the captured image, a first transmission unit (communication unit 34) that transmits the reconstructed image to the server, an information reception unit (communication unit 34) that receives information about voids contained in the reconstructed image from the server, and an output unit (control unit 31) that outputs information about the voids. The server (image processing device 4) includes an extraction unit (control unit 41) that extracts defects in the object based on the reconstructed image, a discrimination unit (control unit 41) that discriminates the type of void contained in the defect, and a second transmission unit (communication unit 42) that transmits information about the discriminated voids to the X-ray Talbot imaging device, so that more detailed information about defects in the object containing fibers and resin can be output.
　また、プログラムは、繊維と樹脂とを含有する被写体をＸ線タルボ撮影装置１で撮影し得られた画像の画像処理装置２のコンピューターを、画像に基づいた再構成画像を取得する画像取得部（制御部２１）、再構成画像に基づいて、被写体内の欠陥を抽出する抽出部（制御部２１）、欠陥に含まれるボイドの種類を判別する判別部（制御部２１）、判別したボイドに関する情報を出力する出力部（制御部２１）、として機能させることで、繊維と樹脂とを含有する被写体の欠陥に関する情報をより詳細に出力できる。 The program also causes the computer of the image processing device 2, which processes an image obtained by photographing an object containing fibers and resin with the X-ray Talbot imaging device 1, to function as an image acquisition unit (control unit 21) that acquires a reconstructed image based on the image, an extraction unit (control unit 21) that extracts defects in the object based on the reconstructed image, a discrimination unit (control unit 21) that discriminates the type of void contained in the defects, and an output unit (control unit 21) that outputs information related to the discriminated voids, thereby making it possible to output more detailed information related to defects in the object containing fibers and resin.
　以上、本発明の実施形態について説明したが、上述した本実施形態における記述は、本発明に係る好適な一例であり、これに限定されるものではない。 The above describes an embodiment of the present invention, but the description of the above embodiment is a preferred example of the present invention and is not intended to be limiting.
　例えば、上記では、表示部２３を備える画像処理装置２は、画像表示装置としても機能しているが、画像処理装置と画像表示装置を別の装置としてもよい。具体的には、画像表示装置では表示処理のみ行い、各種処理等や、繊維凝集等の情報の管理は別の画像処理装置で行ってもよい。例えば、画像処理装置をクラウドとし、表示処理のみ画像表示装置で行うことなどが挙げられる。 For example, in the above, the image processing device 2 equipped with the display unit 23 also functions as an image display device, but the image processing device and the image display device may be separate devices. Specifically, the image display device may only perform display processing, and various processes and management of information such as fiber aggregation may be performed by a separate image processing device. For example, the image processing device may be a cloud, and only display processing may be performed by the image display device.
　また、上記の説明では、本発明に係るプログラムのコンピューター読み取り可能な媒体としてハードディスクや半導体の不揮発性メモリー等を使用した例を開示したが、この例に限定されない。その他のコンピューター読み取り可能な媒体として、ＣＤ－ＲＯＭ等の可搬型記録媒体を適用することが可能である。 In addition, in the above explanation, examples have been disclosed in which a hard disk or a non-volatile semiconductor memory is used as a computer-readable medium for the program according to the present invention, but the present invention is not limited to this example. Portable recording media such as a CD-ROM can also be used as other computer-readable media.
　その他、各装置の細部構成及び細部動作に関しても、発明の趣旨を逸脱することのない範囲で適宜変更可能である。 In addition, the detailed configuration and operation of each device may be modified as appropriate without departing from the spirit of the invention.
　本開示は、画像処理方法、画像処理装置、画像処理システム及びプログラムに利用できる。 This disclosure can be used in image processing methods, image processing devices, image processing systems, and programs.
１　Ｘ線タルボ撮影装置
２　画像処理装置
２１　制御部（画像取得部、抽出部、判別部、出力部）
２２　操作部
２３　表示部
２４　通信部
２５　記憶部
３　Ｘ線タルボ撮影装置
３１　制御部（画像取得部、出力部）
３２　操作部
３３　表示部
３４　通信部（第１送信部、情報受信部）
３５　記憶部
３６　撮影部
４　画像処理装置
４１　制御部（抽出部、判別部）
４２　通信部（第２送信部）
４３　記憶部
１００　Ｘ線撮影システム
２００　Ｘ線撮影システム
Ｈ　被写体
Ｓ　スリット
Ｍｏ　モアレ画像 1 X-ray Talbot imaging device 2 Image processing device 21 Control unit (image acquisition unit, extraction unit, discrimination unit, output unit)
22 Operation unit 23 Display unit 24 Communication unit 25 Storage unit 3 X-ray Talbot imaging device 31 Control unit (image acquisition unit, output unit)
32 Operation unit 33 Display unit 34 Communication unit (first transmission unit, information receiving unit)
35 Storage unit 36 Photographing unit 4 Image processing device 41 Control unit (extraction unit, discrimination unit)
42 Communication unit (second transmission unit)
43 Storage unit 100 X-ray imaging system 200 X-ray imaging system H Subject S Slit Mo Moire image

Claims (18)

  1. 　繊維と樹脂とを含有する被写体をＸ線タルボ撮影装置で撮影し得られた画像の画像処理方法であって、
    　前記画像に基づいた再構成画像を取得する画像取得ステップと、
    　前記再構成画像に基づいて、前記被写体における欠陥を抽出する抽出ステップと、
    　前記欠陥に含まれるボイドの種類を判別する判別ステップと、
    　前記判別したボイドに関する情報を出力する出力ステップと、
    　を有する画像処理方法。     1. An image processing method for an image obtained by photographing an object containing fibers and resin with an X-ray Talbot imaging device, comprising:
    an image acquisition step of acquiring a reconstructed image based on the image;
    an extraction step of extracting a defect in the object based on the reconstructed image;
    a determining step of determining a type of void contained in the defect;
    an output step of outputting information about the determined voids;
    An image processing method comprising the steps of:
  2. 　前記ボイドの種類には、繊維間ボイド及び／または繊維間外ボイドが含まれる請求項１に記載の画像処理方法。 The image processing method according to claim 1, wherein the types of voids include interfiber voids and/or extra-interfiber voids.
  3. 　前記判別ステップは、前記欠陥のうち、前記繊維の近傍にあるボイドを繊維間ボイドとして判別する請求項１に記載の画像処理方法。 The image processing method according to claim 1, wherein the discrimination step discriminates, among the defects, voids that are in the vicinity of the fibers as interfiber voids.
  4. 　前記繊維間ボイドは、前記繊維に対する前記樹脂の含浸不良によるボイドである請求項３に記載の画像処理方法。 The image processing method according to claim 3, wherein the interfiber voids are voids caused by insufficient impregnation of the resin into the fibers.
  5. 　前記繊維間ボイドは、繊維束内または繊維凝集内のボイド、あるいは繊維間、繊維束間、または繊維凝集間のボイドである請求項３に記載の画像処理方法。 The image processing method according to claim 3, wherein the interfiber voids are voids within fiber bundles or fiber clumps, or voids between fibers, fiber bundles, or fiber clumps.
  6. 　前記再構成画像は、微分位相画像を含む請求項１に記載の画像処理方法。 The image processing method according to claim 1, wherein the reconstructed image includes a differential phase image.
  7. 　前記再構成画像は、散乱強度画像を含む請求項６に記載の画像処理方法。 The image processing method according to claim 6, wherein the reconstructed image includes a scattering intensity image.
  8. 　前記再構成画像は、吸収画像を含む請求項７に記載の画像処理方法。 The image processing method according to claim 7, wherein the reconstructed image includes an absorption image.
  9. 　前記再構成画像は、再構成画像のうち、２つ以上の画像を合成した合成画像を含む請求項１に記載の画像処理方法。 The image processing method according to claim 1, wherein the reconstructed image includes a composite image obtained by combining two or more reconstructed images.
  10. 　前記出力ステップは、判別したボイドの種類を出力する請求項２に記載の画像処理方法。 The image processing method according to claim 2, wherein the output step outputs the type of void that has been determined.
  11. 　前記出力ステップは、前記ボイドの個数、大きさ、サイズごとの個数、ボイド間の距離、最大密度面積、面内分布均一性の少なくとも一つの情報を、判別したボイドの種類別に出力する請求項１０に記載の画像処理方法。 The image processing method according to claim 10, wherein the output step outputs at least one of information regarding the number of voids, size, number of voids by size, distance between voids, maximum density area, and in-plane distribution uniformity for each type of void identified.
  12. 　前記判別ステップは、前記欠陥に含まれるクラックと繊維凝集を判別し、
    　前記出力ステップは、前記判別したクラックと繊維凝集に関する情報を出力する請求項１に記載の画像処理方法。     The discrimination step discriminates between a crack and a fiber aggregate included in the defect,
    The image processing method according to claim 1 , wherein the output step outputs information regarding the determined cracks and fiber aggregations.
  13. 　前記出力ステップは、前記繊維間ボイドに該当しないボイドである繊維間外ボイドに関する情報を出力する請求項２に記載の画像処理方法。 The image processing method according to claim 2, wherein the output step outputs information about extra-interfiber voids that are voids that do not correspond to the interfiber voids.
  14. 　前記抽出ステップは、前記再構成画像の信号強度に基づくフィルタ処理により前記欠陥を抽出する請求項１に記載の画像処理方法。 The image processing method according to claim 1, wherein the extraction step extracts the defect by filtering based on the signal intensity of the reconstructed image.
  15. 　前記Ｘ線タルボ撮影装置は、Ｘ線タルボＣＴ装置であり、
    　前記画像は、前記Ｘ線タルボＣＴ装置で前記被写体の奥行方向を断層撮影することで得られる画像である請求項１に記載の画像処理方法。     the X-ray Talbot imaging device is an X-ray Talbot CT device,
    The image processing method according to claim 1 , wherein the image is an image obtained by performing tomography in a depth direction of the subject using the X-ray Talbot CT device.
  16. 　繊維と樹脂とを含有する被写体をＸ線タルボ撮影装置で撮影し得られた画像の画像処理装置であって、
    　前記画像に基づいた再構成画像を取得する画像取得部と、
    　前記再構成画像に基づいて、前記被写体内の欠陥を抽出する抽出部と、
    　前記欠陥に含まれるボイドの種類を判別する判別部と、
    　前記判別したボイドに関する情報を出力する出力部と、
    　を備える画像処理装置。     An image processing device for processing an image obtained by photographing an object containing fibers and resin with an X-ray Talbot imaging device, comprising:
    an image acquisition unit for acquiring a reconstructed image based on the image;
    an extraction unit that extracts defects in the object based on the reconstructed image;
    A discrimination unit that discriminates the type of void contained in the defect;
    an output unit that outputs information about the determined voids;
    An image processing device comprising:
  17. 　Ｘ線タルボ撮影装置とサーバーとを備える画像処理システムであって、
    　前記Ｘ線タルボ撮影装置は、
    　繊維と樹脂とを含有する被写体を撮影する撮影部と、
    　前記撮影した画像に基づいた再構成画像を取得する画像取得部と、
    　前記再構成画像を前記サーバーに送信する第１送信部と、
    　前記再構成画像に含まれるボイドに関する情報を前記サーバーから受信する情報受信部と、
    　前記ボイドに関する情報を出力する出力部と、
    　を備え、
    　前記サーバーは、
    　前記再構成画像に基づいて、前記被写体内の欠陥を抽出する抽出部と、
    　前記欠陥に含まれるボイドの種類を判別する判別部と、
    　前記判別したボイドに関する情報を前記Ｘ線タルボ撮影装置に送信する第２送信部と、
    　を備える画像処理システム。     An image processing system including an X-ray Talbot imaging device and a server,
    The X-ray Talbot imaging device comprises:
    an imaging unit that images an object containing fibers and a resin;
    an image acquisition unit for acquiring a reconstructed image based on the captured image;
    a first transmission unit that transmits the reconstructed image to the server;
    an information receiving unit that receives information regarding voids included in the reconstructed image from the server;
    an output unit that outputs information about the void;
    Equipped with
    The server,
    an extraction unit that extracts defects in the object based on the reconstructed image;
    A discrimination unit that discriminates the type of void contained in the defect;
    a second transmission unit that transmits information about the determined void to the X-ray Talbot imaging device;
    An image processing system comprising:
  18. 　繊維と樹脂とを含有する被写体をＸ線タルボ撮影装置で撮影し得られた画像の画像処理装置のコンピューターを、
    　前記画像に基づいた再構成画像を取得する画像取得部、
    　前記再構成画像に基づいて、前記被写体内の欠陥を抽出する抽出部、
    　前記欠陥に含まれるボイドの種類を判別する判別部、
    　前記判別したボイドに関する情報を出力する出力部、
    　として機能させるプログラム。     A computer of an image processing device for an image obtained by photographing an object containing fibers and resin with an X-ray Talbot imaging device,
    an image acquisition unit for acquiring a reconstructed image based on the image;
    an extraction unit that extracts defects in the object based on the reconstructed image;
    A discrimination unit that discriminates the type of void contained in the defect;
    an output unit that outputs information about the determined voids;
    A program that functions as a
PCT/JP2023/043708 2022-12-14 2023-12-06 Image processing method, image processing device, image processing system, and program WO2024128101A1 (en)

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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2019184450A (en) * 2018-04-12 2019-10-24 コニカミノルタ株式会社 X-ray imaging system
JP2020187088A (en) * 2019-05-17 2020-11-19 コニカミノルタ株式会社 Inspection device and method for generating image
WO2020246220A1 (en) * 2019-06-04 2020-12-10 コニカミノルタ株式会社 Radiography system and enlarged absorption contrast image generation method
JP2021089195A (en) * 2019-12-04 2021-06-10 コニカミノルタ株式会社 Device and method for supporting molding

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2019184450A (en) * 2018-04-12 2019-10-24 コニカミノルタ株式会社 X-ray imaging system
JP2020187088A (en) * 2019-05-17 2020-11-19 コニカミノルタ株式会社 Inspection device and method for generating image
WO2020246220A1 (en) * 2019-06-04 2020-12-10 コニカミノルタ株式会社 Radiography system and enlarged absorption contrast image generation method
JP2021089195A (en) * 2019-12-04 2021-06-10 コニカミノルタ株式会社 Device and method for supporting molding

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