WO2014094815A1 - Korrespondenzanalyseverfahren - Google Patents
Korrespondenzanalyseverfahren Download PDFInfo
- Publication number
- WO2014094815A1 WO2014094815A1 PCT/EP2012/075747 EP2012075747W WO2014094815A1 WO 2014094815 A1 WO2014094815 A1 WO 2014094815A1 EP 2012075747 W EP2012075747 W EP 2012075747W WO 2014094815 A1 WO2014094815 A1 WO 2014094815A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- intensity data
- analysis area
- pixel
- angle
- data
- Prior art date
Links
- 238000004458 analytical method Methods 0.000 title claims abstract description 71
- 238000005286 illumination Methods 0.000 claims abstract description 41
- 239000000835 fiber Substances 0.000 claims abstract description 33
- 230000000737 periodic effect Effects 0.000 claims abstract description 14
- 230000003287 optical effect Effects 0.000 claims abstract description 11
- 238000000034 method Methods 0.000 claims description 36
- 239000002657 fibrous material Substances 0.000 claims description 24
- 238000001514 detection method Methods 0.000 claims description 16
- 238000011156 evaluation Methods 0.000 claims description 14
- 229920000049 Carbon (fiber) Polymers 0.000 claims description 6
- 239000004917 carbon fiber Substances 0.000 claims description 6
- 239000003365 glass fiber Substances 0.000 claims description 5
- 229920002994 synthetic fiber Polymers 0.000 claims description 5
- 239000012209 synthetic fiber Substances 0.000 claims description 5
- 239000000463 material Substances 0.000 abstract description 3
- 238000004519 manufacturing process Methods 0.000 description 13
- 238000011161 development Methods 0.000 description 8
- 230000018109 developmental process Effects 0.000 description 8
- 238000005259 measurement Methods 0.000 description 8
- 239000004744 fabric Substances 0.000 description 6
- 239000004033 plastic Substances 0.000 description 5
- 229920003023 plastic Polymers 0.000 description 5
- 238000012360 testing method Methods 0.000 description 5
- 239000004753 textile Substances 0.000 description 5
- 238000003860 storage Methods 0.000 description 4
- 238000004886 process control Methods 0.000 description 3
- 238000012545 processing Methods 0.000 description 3
- 238000000275 quality assurance Methods 0.000 description 3
- 229920002430 Fibre-reinforced plastic Polymers 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- 239000011151 fibre-reinforced plastic Substances 0.000 description 2
- 239000000047 product Substances 0.000 description 2
- 238000011002 quantification Methods 0.000 description 2
- 239000011265 semifinished product Substances 0.000 description 2
- 238000010998 test method Methods 0.000 description 2
- 238000002604 ultrasonography Methods 0.000 description 2
- 239000000654 additive Substances 0.000 description 1
- 230000000996 additive effect Effects 0.000 description 1
- 238000009954 braiding Methods 0.000 description 1
- 239000002131 composite material Substances 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000007796 conventional method Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000000151 deposition Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000003709 image segmentation Methods 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 239000010410 layer Substances 0.000 description 1
- 230000010287 polarization Effects 0.000 description 1
- 238000002360 preparation method Methods 0.000 description 1
- 239000002356 single layer Substances 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 239000013598 vector Substances 0.000 description 1
- 238000009941 weaving Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/40—Analysis of texture
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/70—Determining position or orientation of objects or cameras
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/40—Extraction of image or video features
- G06V10/42—Global feature extraction by analysis of the whole pattern, e.g. using frequency domain transformations or autocorrelation
- G06V10/435—Computation of moments
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
- G06T2207/30124—Fabrics; Textile; Paper
Definitions
- test system based on industrial image processing. This process automates the detection and quantification of damage to textile fabrics such as gaps or fuzzballs. In this case, an image segmentation with threshold value method takes place.
- the directional determination of the fibers is derived gradient based based on the gap orientation.
- the results are prepared in the form of quality maps in order to allow optimum utilization of the textile fabrics when they are cut.
- the only fabrics investigated are multiaxial fabrics made of carbon fibers with their typical types of damage (gaps or angular deviations).
- Another prototypical system relies on a combination of individual images, which are recorded by sequential illumination of the image scene from eight different directions over an angular range of 180 ° in order to filter out or selectively use disturbing reflections in the individual images to be coupled from the direction of illumination derive the fiber orientation of the respective reflection of the material. Orientations can be distinguished by this system for testing purposes.
- known methods such as the methods known from AT 12 106 Ul or US Pat. No. 6,711,293, are not suitable for unambiguously assigning quasi-periodic structures, such as semi-finished fiber products.
- Quasi-optical structures have no classical object features such as object edges, holes, so that typical methods, such as a block matching, can not be used. It is therefore an object of the invention to enable a measurement of 3-dimensional structures of textured fiber materials. It is a further object of the invention to detect an anisotropic texture. The object is achieved by a correspondence analysis method for providing data relating to the determination of location and direction of locally periodic structures in an analysis area, in particular of fibers of a textured fiber material.
- the method comprises a step of illuminating and detecting the analysis area by means of an optical recording device, wherein the illumination is diffuse, and wherein the detection of the analysis area is performed at a first angle to the diffuse illumination, wherein first pixel-based intensity data of the analysis area are provided , Furthermore, the method comprises the step of illuminating and detecting the analysis area by means of an optical recording device, wherein the illumination is diffuse, and wherein the detection of the analysis area is performed at a second angle to the diffuse illumination, whereby second pixel-based intensity data of the analysis area are made available, wherein the first angle and the second angle are different in 3-dimensional space with respect to the diffuse illumination. Subsequently, intensity correlations are determined from the first intensity data and the second intensity data. Furthermore, at least one further correlation, selected from an orientation correlation and / or a coherence correlation, is determined from the first and second intensity data, wherein the further correlation is determined by means of a structure tensor from the first intensity data and the second intensity data.
- This method makes it possible to provide a test method which can already be used in the manufacturing process for quality assurance.
- the method according to the invention allows a production-integrated test, in particular with regard to the storage and filing quality in the production of plastic components by means of textured fiber materials in 3-dimensional terms. Due to the design also the stringent requirements under industrial conditions (short cycle times, robustness, reliability, etc.) can be met, i. a feedback of the measurement results for corrective process intervention (process control) is made possible.
- a structure tensor of a pixel of the pixel-based intensity data is made up of at least the pixels directly adjacent to this pixel certainly.
- the method can be implemented and parallelized in a particularly simple manner.
- disparities are determined on the basis of the first and second intensity data and at least one selected from orientation data and / or coherence data. This makes it particularly easy to derive unique data.
- depth information is extracted. This makes it particularly easy to derive 3-dimensional unique data.
- the position and orientation of periodic structures in 3-dimensional space is determined on the basis of the depth information and the structure tensor. This allows unambiguous values to be determined even for quasiperiodic structures.
- the textured fiber material is selected from a woven, laid or braided fiber material, fibers having glass fibers, carbon fibers, natural fibers or synthetic fibers.
- a device for a correspondence analysis method for providing data relating to the determination of location and direction of locally periodic structures in an analysis area, in particular of fibers of a textured fiber material.
- the device has at least one illumination device for illuminating the analysis area, wherein the illumination is diffuse, at least one optical recording device for detecting the analysis area, wherein the detection of the analysis area is made at an angle to the diffuse illumination, at least one memory device for storing first pixel-based intensity data of the Analysis area and second pixel-based intensity data of the analysis area, the first pixel-based intensity data originating from a detection of the analysis area at a first angle to the diffuse illumination and the second pixel-based intensity data coming from a detection of the analysis area at a second angle to the diffuse illumination, wherein the first angle and the second angle in the 3-dimensional space is different with respect to the diffuse illumination, at least one evaluation device for determining intensity Correlations from the first intensity data and the second intensity data, on.
- the evaluation device is furthermore equipped to determine from the first and second intensity data at least one further correlation, selected from an orientation correlation and / or a coherence correlation, wherein the further correlation is determined by means of a structure tensor from the first intensity data and the second intensity data.
- the device according to the invention allows a production-integrated test, in particular with respect to the storage and filing quality in the production of plastic components by means of textured fiber materials in 3-dimensional terms. Due to the design also the stringent requirements under industrial conditions (short cycle times, robustness, reliability, etc.) can be met, i. a feedback of the measurement results for corrective process intervention (process control) is made possible.
- a structure tensor of a pixel of the pixel-based intensity data is determined from at least the pixels directly adjacent to this pixel.
- the evaluation device is equipped to determine disparities on the basis of the first and second intensity data and at least one selected from orientation data and / or coherence data. This makes it particularly easy to derive unique data.
- the evaluation device is equipped to extract depth information. This makes it particularly easy to derive 3-dimensional unambiguous data.
- the evaluation device is furthermore equipped to determine the position and orientation of periodic structures in 3-dimensional space on the basis of the depth information and the structure tensor. This allows unambiguous values to be determined even for quasiperiodic structures.
- the textured fiber material is selected from a woven, laid or braided fiber material, fibers having glass fibers, carbon fibers, natural fibers or synthetic fibers. As a result, all types of technical fabrics can be detected.
- FIG. 1 shows images of an analysis area of a quasi-periodic structure from two different angles with ambiguous correspondences on the basis of a gray value correlation
- FIG. 3 shows unambiguous correspondences of points in the images of the analysis region of the quasi-periodic structure at two different angles on the basis of the invention
- FIG. 6 shows an exemplary arrangement of pixels when calculating a pattern tensor according to embodiments of the invention
- FIG. 8 shows an exemplary representation of ascertained coherences based on the section of the analysis area.
- FIG. 1 shows in the upper part images of an analysis area A of a quasi-periodic structure from two different angles with ambiguous correspondences based on a gray value correlation.
- the image taken from a first camera position K x and on the right side, for example, the image taken from a first camera position K 2 are shown.
- An example of such possible camera positions is given in FIG.
- An exemplary point P is selected on the left image.
- This point may be associated with conventional methods, no clear corresponding point on the right image, but instead are exemplary points Z lt Z 2, Z 3 indicated as a possible correspondence points.
- the cause of this ambiguity is a quasiperiodic structure of the surface. If one tries to form a gray value correlation, as shown in the lower right part of FIG. 1, then a large number of maxima with similar amplitudes can be established. In the result is So no clear correspondence can be determined. Since no clear correspondence can be determined, it is not possible in the sequence to create a 3-dimensional assignment of the data.
- the stated method allows to overcome the otherwise encountered ambiguity of quasi-periodic structures of the surface. As a result, a clear correspondence can be determined. Since a clear correspondence can be determined, it is also possible subsequently to create a 3-dimensional assignment of the data.
- an exemplary method according to FIG. 4 is used, for example, with an exemplary arrangement according to FIG. 5.
- this correspondence analysis method for providing data relating to the determination of location and direction of locally periodic structures in an analysis area A, in particular of fibers of a textured fiber material
- a first step 100 the analysis area A is illuminated by means of a diffuse illumination L and by means of an optical recording device K x recorded.
- the detection of the analysis area A takes place at a first angle to the diffuse illumination L, wherein first pixel-based intensity data of the analysis area A are made available.
- An exemplary illumination L can be done by commercially available lighting devices.
- the arrangement of the exemplary illumination may be substantially perpendicular to the analysis area A, but is not limited thereto.
- an optical recording device can serve as a camera.
- the analysis area A is re-illuminated by means of a second diffuse illumination or the same diffuse illumination L.
- the analysis area A is in turn detected by the same optical recording device K x or a second optical recording device K 2 , wherein the detection of the analysis area A at a second angle to the diffuse Illumination L is made, wherein second pixel-based intensity data of the analysis area are provided, wherein the first angle and the second angle in the 3-dimensional space are different with respect to the diffuse illumination.
- intensity correlations are now determined from the first intensity data and the second intensity data.
- At least one further correlation selected from an orientation correlation and / or a coherence correlation, is now determined within the method according to the invention in a step 400, the further correlation being determined by means of a structure tensor from the first intensity data and the second intensity data.
- These properties of the quasi-periodic surface can be translated into other features of the surface, such as e.g. an orientation of the quasi-periodic structure, a size of the quasi-periodic structure, a coherence measure of the quasi-periodic structure are mapped.
- orientation e.g. Statements about anisotropic properties of a quasi-periodic structure are taken.
- An exemplary joint evaluation can be achieved by an additive or multiplicative link, possibly with the aid of a weighting.
- the invention makes use of the fact that the texture, i. the microform, which is a superposition to the surface of the macro-shape. Features of this fiber texture, such. As the texture orientation, are thus substantially in the plane of the macro-shape of the surface.
- a texture tensor of a pixel P of the pixel-based intensity data is determined from at least the pixels N directly adjacent to that pixel P. That is, a pixel of a captured image is associated with values from the pixel neighborhood. For example, all immediately adjacent pixels, ie 8 pixels N. ⁇ ... N n or else more distant pixels, eg 24 pixels N ... N are taken into account in the calculation.
- pixel arrangement reference is made to FIG.
- Figure 7 shows an exemplary representation of determined orientations based on a section of the analysis area.
- the determined orientation is shown in each case for a pixel as an arrow above the associated gray value of the pixel.
- the orientation can be given not only as a direction but also as a gradient.
- FIG. 8 shows an example representation of determined coherences based on the section of the analysis area.
- the determined coherence is again indicated in each case for a pixel as a gray value.
- Both Figure 7 and Figure 8 are based on data obtained from first and second intensity data. For better illustration of the orientation arrows in FIG. 7, however, the intensity data of several pixels have been weighted, so that the arrow density is lower.
- the ascertained correlations differ from the original intensity data, so that differences that were previously unrecognizable from the intensity data can be used for the assignment.
- disparities can be determined. This makes it possible to extract depth information from the data. In this way, the position and orientation of (quasi-) periodic structures in 3-dimensional space can be determined on the basis of the depth information and the structure tensor.
- FIG. 3 shows unambiguous correspondences of points in the images of the analysis area A of the quasi-periodic structure from two different angles on the basis of the invention, analogous to the images in FIG.
- FIG. 5 shows an exemplary arrangement according to the invention.
- a device for a correspondence analysis method for providing data relating to the determination of location and direction of locally periodic structures in an analysis area A, in particular of fibers of a textured fiber material.
- the device has at least one illumination device L for illuminating the analysis area, the illumination being diffuse.
- the device has one or two receiving devices.
- a receiving device can be moved by means of a positioning device to different locations and in different solid angles, or there are two recording devices provided at different spatial angles at different locations.
- a receiving device may also have substantially the same angle as the illumination device L to the analysis area A.
- the device has at least one memory device MEM for storing first pixel-based intensity data of the analysis area and second pixel-based intensity data of the analysis area, the first pixel-based intensity data originating from a detection of the analysis area at a first angle to the diffuse illumination and the second pixel-based intensity data coming from a detection of the Analysis area at a second angle to the diffuse illumination, wherein the first angle and the second angle in the 3-dimensional space with respect to the diffuse illumination are different, and at least one evaluation CPU for determining intensity correlations of the first intensity data and the second Intensity data, on.
- the evaluation device CPU is further equipped to determine from the first and second intensity data at least one further correlation, selected from an orientation correlation and / or a coherence correlation, the further correlation being determined by means of a structure tensor from the first intensity data and the second intensity data ,
- the invention provides a photogrammetry system which is capable of measuring a fiber orientation of the material having a quasi-periodic surface in 3-dimensional space even within a processing machine. For this, e.g. Local 2-dimesional surfaces are measured with two independent calibrated cameras, which are combined to form a 3-dimesional surface orientation of the quasiperiodic surface using the new correspondence analysis method.
- correspondence vectors are first formed, with a pixel-wise assignment of the correspondences. Subsequently, the depth information can be extracted. Subsequently, a 3D fiber orientation can be derived from the results.
- the invention relates to a method for the simultaneous detection of the geometry and the anisotropy of a 3-dimensional surface, comprising the steps of capturing two images of the surface from different spatial directions, determining texture features of the surface in both images, photogrammetric combination of both surface images to the geometry of the 3-dimensional Surface using the previously determined texture features and back projection of the texture features on the previously determined 3-dimensional surface to calculate the anisotropy of the same.
- the invention provides a method and apparatus that allows for an integrated 3-dimensional geometry and fiber orientation measurement for quality assured and automated fiber composite production.
- the invention makes it possible to determine the 3-dimensional geometry (macrogeometry) as well as the fiber orientation (texture feature or microgeometry) with a sufficiently low measurement uncertainty integrated in production.
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- Computer Vision & Pattern Recognition (AREA)
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- General Physics & Mathematics (AREA)
- Computing Systems (AREA)
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- Quality & Reliability (AREA)
- Treatment Of Fiber Materials (AREA)
Abstract
Description
Claims
Priority Applications (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
PCT/EP2012/075747 WO2014094815A1 (de) | 2012-12-17 | 2012-12-17 | Korrespondenzanalyseverfahren |
DE112012007227.8T DE112012007227A5 (de) | 2012-12-17 | 2012-12-17 | Korrespondenzanalyseverfahren |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
PCT/EP2012/075747 WO2014094815A1 (de) | 2012-12-17 | 2012-12-17 | Korrespondenzanalyseverfahren |
Publications (1)
Publication Number | Publication Date |
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WO2014094815A1 true WO2014094815A1 (de) | 2014-06-26 |
Family
ID=47504912
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/EP2012/075747 WO2014094815A1 (de) | 2012-12-17 | 2012-12-17 | Korrespondenzanalyseverfahren |
Country Status (2)
Country | Link |
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DE (1) | DE112012007227A5 (de) |
WO (1) | WO2014094815A1 (de) |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20170330350A1 (en) * | 2014-12-19 | 2017-11-16 | Hewlett-Packard Development Company, L.P. | Determine image capture position information based on a quasi-periodic pattern |
US20230324310A1 (en) * | 2019-05-21 | 2023-10-12 | Columbia Insurance Company | Methods and systems for measuring the texture of carpet |
Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US6711293B1 (en) | 1999-03-08 | 2004-03-23 | The University Of British Columbia | Method and apparatus for identifying scale invariant features in an image and use of same for locating an object in an image |
AT12106U1 (de) | 2010-09-17 | 2011-10-15 | Profactor Gmbh | Verfahren und vorrichtung zur untersuchung von oberflächen |
-
2012
- 2012-12-17 WO PCT/EP2012/075747 patent/WO2014094815A1/de active Application Filing
- 2012-12-17 DE DE112012007227.8T patent/DE112012007227A5/de not_active Withdrawn
Patent Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US6711293B1 (en) | 1999-03-08 | 2004-03-23 | The University Of British Columbia | Method and apparatus for identifying scale invariant features in an image and use of same for locating an object in an image |
AT12106U1 (de) | 2010-09-17 | 2011-10-15 | Profactor Gmbh | Verfahren und vorrichtung zur untersuchung von oberflächen |
Non-Patent Citations (1)
Title |
---|
KRAUSE M ET AL: "Determination of the fibre orientation in composites using the structure tensor and local X-ray transform", JOURNAL OF MATERIALS SCIENCE, KLUWER ACADEMIC PUBLISHERS, BO, vol. 45, no. 4, 17 November 2009 (2009-11-17), pages 888 - 896, XP019770433, ISSN: 1573-4803 * |
Cited By (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20170330350A1 (en) * | 2014-12-19 | 2017-11-16 | Hewlett-Packard Development Company, L.P. | Determine image capture position information based on a quasi-periodic pattern |
US10521931B2 (en) * | 2014-12-19 | 2019-12-31 | Hewlett-Packard Development Company, L.P. | Determine image capture position information based on a quasi-periodic pattern |
US11263784B2 (en) | 2014-12-19 | 2022-03-01 | Hewlett-Packard Development Company, L.P. | Determine image capture position information based on a quasi-periodic pattern |
US20230324310A1 (en) * | 2019-05-21 | 2023-10-12 | Columbia Insurance Company | Methods and systems for measuring the texture of carpet |
Also Published As
Publication number | Publication date |
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DE112012007227A5 (de) | 2015-09-24 |
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