CN112945988B - Lens defect detection system and detection method - Google Patents
Lens defect detection system and detection method Download PDFInfo
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- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
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- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
- G01N2021/8887—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges based on image processing techniques
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Abstract
The invention relates to a lens defect detection system and a lens defect detection method, wherein the lens defect detection system comprises an imaging unit (2), a coaxial light source (3), a dome light source (4), an annular light source (5) and a backlight light source (6) which are sequentially arranged, the imaging unit (2), the coaxial light source (3), the dome light source (4), the annular light source (5) and the backlight light source (6) are coaxially arranged, and the dome light source (4) and the annular light source (5) are alternately arranged. The lens defect detection system and the detection method have the advantages of high detection accuracy, wide application range and low omission factor.
Description
Technical Field
The invention relates to the technical field of optics, in particular to a lens defect detection system and a detection method.
Background
The application range of the mobile phone camera module in the current market is wider and wider, the requirements of customers on the quality of the camera module are higher and higher, and the surface defects of the lenses in the camera module greatly determine the quality of the imaging of the mobile phone camera module. The main optical form of the mobile phone lens is an aspheric lens, and in order to ensure the imaging effect, defect detection is usually required to be carried out on the upper surface and the lower surface of the lens. The requirement for the optical system and the detection algorithm of the automatic detection device is high because of the variety of defects. Currently, in the industry, a lens detection device generally adopts an upper annular light source and a lower annular light source for illumination, and adopts a scheme of single image taking, which has the following defects:
1. the illumination mode of the upper light source and the lower light source can cause poor imaging effect of partial light dirt, light scratch and black spots, and can easily cause missed detection.
2. By adopting a scheme of single drawing, defects such as white spots, demolding and the like cannot be effectively distinguished, and particularly, the omission ratio is higher for small-size (within 30 mu m) demolding.
3. When the lens with larger thickness is detected, the partial area defocusing phenomenon exists, so that the defects of white spots, demolding and the like are formed and the imaging blurring causes the over-detection problem, and the imaging effect of shallow dirt and scratch is weakened to cause the omission detection problem.
4. The defect detection adopts a fixed threshold value or dynamic threshold value dividing method, and has high defect omission rate such as shallow dirt, stripping and the like.
Disclosure of Invention
The invention aims to solve the problems, and provides a lens defect detection system and a defect detection method, which solve the problem of high omission factor of the existing detection equipment and detection method.
In order to achieve the above object, the present invention provides a lens defect detection system, which comprises an image capturing unit, a coaxial light source, a dome light source, an annular light source and a backlight light source which are sequentially arranged, wherein the image capturing unit, the coaxial light source, the dome light source, the annular light source and the backlight light source are coaxially arranged, and the dome light source and the annular light source are alternately arranged.
According to one aspect of the invention, the dome light source is provided with a connection plate, and the coaxial light source is fixedly supported on the connection plate.
According to one aspect of the invention, the light emitting surface of the coaxial light source and the light transmitting hole on the dome light source are in a proportion relationship of two times or more.
According to one aspect of the invention, the image pickup unit comprises a support plate, a fixed plate arranged on the support plate, an image sensor, a telecentric lens and a driving device, wherein the image sensor and the telecentric lens are coaxially arranged on the fixed plate in sequence, and the driving device is used for driving the fixed plate to move.
According to one aspect of the invention, the backlight light source comprises a diffuser plate having a color set to a complementary color to the light source band colors of the on-axis light source, dome light source and annular light source.
According to one aspect of the present invention, the backlight source includes a diffusion plate, and the diffusion plate is made of a black translucent material.
According to one aspect of the invention, the surface roughness of the diffusion plate is 3.2-25 Ra, and the absorptivity of the diffusion plate to the optical system light source wave band is 70-95.
According to one aspect of the invention, the backlight source further comprises a backlight bead, the diffusion plate is arranged between the backlight bead and the annular light source luminous surface, and the distance between the diffusion plate and the backlight bead is more than 10mm.
The invention also provides a detection method using the detection system, which comprises the following steps: and placing a lens between the dome light source and the annular light source, turning on the coaxial light source, the dome light source and the annular light source, turning off the backlight light source, shooting a conventional image to detect defects, and being beneficial to judging whether surface white spots, film defects, dirt and filigree defects exist.
According to one aspect of the present invention, the defect detection of the regular image further includes detecting whether a shallow defect exists:
dividing the conventional image into a plurality of circular rings with stable gray level change according to the gray level distribution of the lens;
continuously dividing the divided circular ring into equal-divided circular rings with the difference value of the inner radius and the outer radius as a set value;
and calculating the average gray value of the equally divided circular ring, traversing the pixel values on the equally divided circular ring, and judging that the pixel values are shallow defects if the gray value difference exceeds a set threshold value.
According to one aspect of the present invention, the defect detection of the regular image further comprises ghost elimination of the regular image:
carrying out gray stretching on the conventional image to make the gray difference value between the lens area and the frosted area equal, and then carrying out affine transformation to move to a ghost area to obtain a transformed image;
subtracting the conventional image before being processed from the transformed image to remove ghost interference:
Mat res ＝Mat src -a*M 0 *Mat src
wherein Mat res Mat for the resulting image src For ghost images, a is the gray scale stretch factor, M 0 Is an affine transformation matrix.
According to one aspect of the invention, the lens has a diameter of 5mm or less and a thickness of 1mm or less.
The invention also provides a detection method using the detection system, which comprises the following steps:
placing a lens between the dome light source and the annular light source, turning on the coaxial light source, the dome light source and the annular light source, and turning off the backlight light source to shoot a conventional image;
turning on the backlight source, turning off the coaxial light source, the dome light source and the annular light source, and shooting a back field image;
performing defect detection on the conventional image, so as to be beneficial to judging whether surface white spots, film defects, dirt and filigree defects exist;
and detecting the defects of the back field image and judging whether black point defects exist or not.
According to one aspect of the present invention, the defect detection of the regular image and the back field image further includes detecting whether a shallow defect exists:
dividing the conventional image and the back field image into a plurality of circular rings with stable gray level change according to the gray level distribution of the lens;
continuously dividing the divided circular ring into equal-divided circular rings with the difference value of the inner radius and the outer radius as a set value;
and calculating the average gray value of the equally divided circular ring, traversing the pixel values on the equally divided circular ring, and judging that the pixel values are shallow defects if the gray value difference exceeds a set threshold value.
According to one aspect of the present invention, the conventional image further includes performing ghost elimination before performing defect detection:
carrying out gray stretching on the conventional image to make the gray difference value between the lens area and the frosted area equal, and then carrying out affine transformation to move to a ghost area to obtain a transformed image;
subtracting the conventional image before being processed from the transformed image to remove ghost interference:
Mat res ＝Mat src -a*M 0 *Mat src
wherein Mat res Mat for the resulting image src For ghost images, a is the gray scale stretch factor, M 0 Is imitated byThe matrix is transformed.
According to one aspect of the invention, the lens has a diameter of 5-8mm and a thickness of less than 1mm.
The invention also provides a detection method using the detection system, which comprises the following steps:
placing a lens between the dome light source and the annular light source, opening the coaxial light source and the dome light source, closing the annular light source and the backlight light source, and shooting a bright field image;
turning on the annular light source, turning off the coaxial light source, the dome light source and the backlight light source, and shooting a dark field image;
turning on the backlight source, turning off the coaxial light source, the dome light source and the annular light source, and shooting a back field image;
performing defect detection on the bright field image, and being beneficial to judging whether surface white spots, film defects, dirt and white spots are defects or not;
detecting the defects of the dark field image, and judging whether the defects of scratch, hairline and road exist or not;
and detecting the defects of the back field image and judging whether black point defects exist or not.
According to one aspect of the invention, the method further comprises differential image acquisition, which is beneficial to the detection of the demolding defect:
multiplying the bright field image and the dark field image by a set coefficient to obtain a differential image:
Mat sub ＝a*Mat L -b*Mat D
wherein: mat (Mat) L Mat for bright field image D For dark field images, a and b are scale factors, mat sub Is the difference image.
According to one aspect of the present invention, the defect detection of the bright field image, dark field image and back field image further includes detecting whether a shallow defect exists:
dividing the bright field image, the dark field image and the back field image into a plurality of rings with stable gray level change according to the gray level distribution of the lens;
continuously dividing the divided circular ring into equal-divided circular rings with the difference value of the inner radius and the outer radius as a set value;
and calculating the average gray value of the equally divided circular ring, traversing the pixel values on the equally divided circular ring, and judging that the pixel values are shallow defects if the gray value difference exceeds a set threshold value.
According to one aspect of the present invention, before performing defect detection, the method further comprises performing ghost elimination on the bright field image and dark field image:
gray stretching is carried out on the bright field image and the dark field image, so that gray difference values of the lens area and the frosted area are equal, affine transformation is carried out, and then the lens area and the frosted area are moved to a ghost area, and a transformed image is obtained;
subtracting the bright field image and the dark field image before being processed from the respective transformed images respectively to remove ghost interference:
Mat res ＝Mat src -a*M 0 *Mat src
wherein Mat res Mat for the resulting image src For ghost images, a is the gray scale stretch factor, M 0 Is an affine transformation matrix.
According to one aspect of the invention, the lens has a diameter of 8mm or more and a thickness of less than 1mm.
The invention also provides a detection method using the detection system, which comprises the following steps:
placing a lens with the lens thickness larger than the depth of field of the telecentric lens between the dome light source and the annular light source, turning on the coaxial light source, the dome light source and the annular light source, and turning off the backlight light source;
the driving device drives the image sensor and the telecentric lens to move for layer shooting to obtain 2-5 layer shooting images;
and performing defect detection on the obtained photographed images of each layer.
According to one aspect of the invention, defect detection of a layer shot image includes shallow defect detection:
dividing each layer of photographed image into a plurality of rings with stable gray level change according to the gray level distribution of the lens;
continuously dividing the divided circular ring into equal-divided circular rings with the difference value of the inner radius and the outer radius as a set value;
and calculating the average gray value of the equally divided circular ring, traversing the pixel values on the equally divided circular ring, and judging that the pixel values are shallow defects if the gray value difference exceeds a set threshold value.
According to one aspect of the invention, the layered image further comprises, prior to defect detection, ghost elimination:
gray stretching is carried out on each layer of photographed image, gray difference values of the lens area and the frosted area are equal, affine transformation is carried out, and then the images are moved to a ghost area, so that transformed images are obtained;
subtracting the layer shot image before being processed from the transformed image to remove ghost interference:
Mat res ＝Mat src -a*M 0 *Mat src
wherein Mat res Mat for the resulting image src For ghost images, a is the gray scale stretch factor, M 0 Is an affine transformation matrix.
According to one aspect of the invention, the thickness of the lens is not less than 1mm.
The lens defect detection system and the detection method can use different light source combination schemes according to the defect type, and are high in detection accuracy and wide in application range. The detection method provided by the invention comprises the steps of eliminating ghost interference on the conventional image, the bright field image and the dark field image, so that the defect exposure is obvious, the detection accuracy is improved, and the omission ratio is reduced. The detection method further comprises the step of obtaining a differential image through the bright field image and the dark field image so as to effectively distinguish white point defects and demoulding defects, improve the detection capability and reduce the omission ratio. The detection method also comprises a shallow defect detection method, wherein shallow defects are segmented by analyzing the relative change of the gray value of the local area of the lens, so that the detection sensitivity is improved, and the omission ratio is reduced.
Drawings
FIG. 1 schematically illustrates a block diagram of a lens defect detection system according to the present invention;
fig. 2 schematically shows a coaxial light source and dome light source connection diagram according to the invention;
FIG. 3 schematically illustrates a ring light source and backlight combination according to the present invention;
FIG. 4 schematically illustrates a bright field image of a lens;
FIG. 5 schematically illustrates a dark field image of a lens;
FIG. 6 schematically illustrates a back field image of a lens;
FIG. 7 schematically illustrates a conventional image of a lens;
FIG. 8 shows a refractive schematic of an in-line light source;
fig. 9 schematically shows a diagram of a back field image without ghost elimination;
fig. 10 schematically shows a view after ghost elimination of the back field image;
FIG. 11 is a schematic representation of a defect detection method for lenses having a diameter of 5mm or less and a thickness of less than 1 mm;
FIG. 12 schematically illustrates a shallow defect detection method according to the present invention;
FIG. 13 schematically illustrates a defect detection method diagram for a lens having a diameter of 5-8mm and a thickness of less than 1 mm;
FIG. 14 is a schematic representation of a defect detection method for lenses having a diameter of 8mm or more and a thickness of less than 1 mm;
FIG. 15 schematically illustrates imaging in bright field images of white point defects and defects that are film release;
FIG. 16 schematically illustrates imaging in a dark field image according to white point defects;
fig. 17 shows a differential image obtained from a bright field image and a dark field image;
fig. 18 schematically illustrates a defect detection method diagram for a lens having a thickness greater than the depth of field of the telecentric lens.
Detailed Description
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the embodiments will be briefly described below. It is apparent that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained from these drawings without inventive work for those of ordinary skill in the art.
The present invention will be described in detail below with reference to the drawings and the specific embodiments, which are not described in detail herein, but the embodiments of the present invention are not limited to the following embodiments.
Referring to fig. 1, the present invention provides a lens defect detection system, which includes an image capturing unit 2, a coaxial light source 3, a dome light source 4, an annular light source 5, and a backlight light source 6, which are sequentially disposed from top to bottom. In the lens defect detection system of the invention, the camera unit 2, the coaxial unit 3, the dome light source 4, the annular light source 5 and the backlight light source 6 are coaxially arranged in sequence, and the dome light source 4 and the annular light source 5 are alternately arranged. I.e. as shown in fig. 1, there is a space 1 between the dome light source 4 and the ring light source 5, the space 1 being subject to defect detection by the placement of the lens. The defect detection system of two lenses installed on the same mounting board is shown in fig. 1, so that defect detection can be performed on the two lenses at the same time, so as to improve detection efficiency.
The implementation of placing lenses to be inspected at the space 1 is not limited according to the inventive concept, and according to one embodiment of the invention, a workpiece disc is provided at the space 1 between the dome light source 4 and the ring light source 5, on which a lens mounting position is provided for placing lenses to be inspected. According to a second embodiment of the invention, the lens may be mounted on another tool which is inserted at the distance 1 between the dome light source 4 and the annular light source 5 when defect detection is required, so that the lens is detected coaxially with the dome light source 4 and the annular light source 5.
According to an embodiment of the present invention, the image capturing unit 2 of the present invention includes a support plate 21, a fixing plate 22 is mounted on the support plate 21, and a high-quality image sensor 23 and a high-resolution telecentric lens 24 are sequentially mounted on the fixing plate 22. The camera unit 2 further comprises a driving device 25, for example, the driving device 25 can be set as a servo motor, and is used for driving the fixed plate 22 to move so as to realize the movement of the high-quality image sensor 23 and the high-resolution telecentric lens 24, so that the depth of field limitation of the lens can be overcome, clear pictures of different areas of the lens can be shot, and the lens detection device can be suitable for lens detection with the lens thickness larger than the depth of field of a camera.
According to one embodiment of the present invention, the high quality image sensor 23 of the present invention may provide both hardware configurations of a black and white camera or a color camera. Where black and white cameras can provide the vast majority of defect detection functions. The color camera is added with detection items of color anomaly defects based on the black-and-white camera function so as to cope with special defects of partial manufacturers, such as film shortage, film color anomaly and the like.
The coaxial light source 3 and the dome light source 4 are rigidly connected, so that the coaxiality between the light sources can be effectively ensured. Referring to fig. 2, according to an embodiment of the present invention, a connection plate 41 is provided on the dome light source 4 of the present invention, and the coaxial light source 3 is fixedly supported on the connection plate 41 to ensure that the coaxial light source 3 and the dome light source 4 are coaxially disposed.
In addition, in the lens defect detection system, the light emitting surface of the coaxial light source 3 and the light passing hole on the dome light source 4 are in a proportion relation of 2 times or more. This arrangement allows a better supplementary relationship between the coaxial light source 3 and the dome light source.
The lens defect detection system of the present invention is shown in fig. 3, in which the backlight source 6 includes a diffusion plate 61. According to one embodiment of the present invention, the color of the diffusion plate 61 and the light source band colors of the coaxial light source 3, the dome light source 4 and the ring light source 5 are set to complementary colors (e.g., blue and yellow, red and green, etc.), thereby enabling absorption of light energy.
According to the second embodiment of the present invention, the diffusion plate 61 may also be provided as a black translucent material, so that it is compatible with absorbing light source energy of all visible light bands including white light.
In the invention, the color of the diffusion plate 61 and the light source wave band colors of the coaxial light source 3, the dome light source 4 and the annular light source 5 are set to be complementary colors or to be black and semitransparent, so that the backlight light source 6 is not turned on during lens detection, the backlight light source is only used as a background, and the light rays emitted by the coaxial light source 3, the dome light source 4 and/or the annular light source 5 can be absorbed by the diffusion plate and can not be reflected into the telecentric lens 24 and the image sensor 23 by the diffusion plate 61, thereby improving the imaging quality and the accuracy of defect detection.
In the present invention, the surface roughness of the diffusion plate 61 is 3.2. Ltoreq.Ra. Ltoreq.25, which is set so that the surface of the diffusion plate 61 is not reflected and no interference of the uneven texture background occurs. The absorptivity of the diffusion plate 61 in the light source wave band of the optical system is 70% or more and is 95% or less, so that the diffusion plate can be used as a dark field background when the diffusion plate is not lighted on the premise of ensuring the normal transmission of backlight light. As shown in fig. 3, according to an embodiment of the present invention, the ring-shaped light source 5 and the backlight light source 6 are fixedly connected using screws. The backlight source 6 further comprises backlight source beads, the diffusion plate 61 is arranged between the backlight source beads and the annular light source 5 as the light emitting surface of the backlight source 6, and the distance between the diffusion plate 61 and the backlight source beads is more than 10mm, so that the uniformity of the light emitting surface of the backlight source 6 reaches an ideal value (> 90%) after the diffusion plate 61 is penetrated.
The lens defect detection system is sequentially provided with the coaxial light source 3, the dome light source 4, the annular light source 5 and the backlight light source 6, so that different light source combination lighting modes can be adopted for lenses with different specifications to effectively detect different defect types. In addition, set up the camera shooting unit 2 in the top of coaxial light source 3 to camera shooting unit 2 can follow vertical direction and remove, thereby also can carry out defect detection to the lens that lens thickness is greater than the camera lens depth of field, application scope is wide.
In particular, the invention, due to the arrangement of the coaxial light source 3, the dome light source 4, the annular light source 5 and the backlight light source 6, can have different combinations of lighting to highlight different defect characteristics when detecting the lens.
When the on-axis light source 3 and the dome light source 4 are turned on and the ring light source 5 and the backlight light source 6 are turned off, a bright field image can be obtained through the telecentric lens 24. Under the illumination condition, the imaging of reflection defects such as surface film stripping, surface white spots, film shortage, dirt and the like of the lens is obvious. This is because the defects have a low light transmittance, while the non-defective areas of the lens have a relatively high transmittance, so that the gray values of the defective areas are significantly greater than the imaging effect of the non-defective areas of the lens in the image.
When the ring light source 5 is turned on and the on-axis light source 3, the dome light source 4 and the backlight light source 6 are turned off, a dark field image can be obtained through the telecentric lens 24. Under the illumination condition, defects such as surface white spots, scratches, bubbles, hairlines, group white spots, process channels and the like are obvious in imaging. This is due to the diffuse scattering of the ring light passing over the defective surface, such that defective portions are received by telecentric lens 24, while light rays from non-defective areas of the lens are transmitted directly and cannot be received by the telecentric lens.
When the backlight source 6 is turned on and the on-axis light source 3, the dome light source 4, and the ring light source 5 are turned off, one back field image can be obtained through the telecentric lens 24. Under this illumination condition, black spot defect imaging is remarkable. This is because the backlight source is directed at the lens, light from the non-defective portion of the lens is received by the telecentric lens through the lens, and the direct light source is continuously blocked by the black spot defect.
When the on-axis light source 3, the dome light source 4 and the ring light source 5 are turned on, and the backlight light source 6 is turned off, a conventional image can be obtained through the telecentric lens. Under the illumination condition, most defects such as surface stripping, surface white spots, film shortage, dirt, filigree and the like can be imaged.
Fig. 4-7 schematically show diagrams of bright field images, dark field images, back field images and conventional images, respectively, from which it is clear that corresponding defect features are evident under different illumination conditions. Therefore, the lens defect detection system can acquire one or more images by utilizing different illumination condition combinations to detect defects, so that the detection precision is improved.
As shown in connection with fig. 8 and 9, the bright field image, dark field image, and conventional image of the present invention are ghost images, each including a ghost image area and a lens frosting area. Specifically, the coaxial light of the invention turns the light by 90 degrees through the spectroscope on the coaxial light source, and due to the effect of the thickness of the spectroscope glass, the light can be reflected on two surfaces of the spectroscope at the same time in the turning process (the prior film plating technology can not ensure 100% transmittance of the second reflecting surface), wherein the incident light a and the emergent light b of the second reflecting surface are refracted inside the spectroscope and then are emitted from the first reflecting surface, the light c is parallel to but not collinear with the light d directly reflected by the first reflecting surface, and the light finally forms a ghost image after entering the image sensor. The lens defect caused by the interference of the ghost image is not obvious enough and is unfavorable for detection, so that ghost image elimination operation is usually required before the bright field image, the dark field image and the conventional image are detected, the image after ghost image elimination is obtained, and defect detection is carried out, so that the detection accuracy is improved.
The following describes in detail a defect detection method for a lens using the lens defect detection system of the present invention:
the invention provides a lens defect detection method, which is preferably used for detecting the defects of lenses with the diameters less than or equal to 5mm and the thicknesses less than 1mm. As shown in fig. 11, a lens is placed between the dome light source 4 and the ring light source 5 according to the foregoing embodiment or other embodiments, the coaxial light source 3, the dome light source 4 and the ring light source 5 are turned on, and the backlight light source 6 is turned off, and a conventional image is photographed for defect detection. Specifically, preprocessing, image segmentation and BLOB analysis are sequentially carried out on the image, and whether surface white spots, film defects, dirt and hairline defects exist or not is judged according to set various defect standard parameters.
Wherein defect detection of the regular image further comprises detecting whether a shallow defect is present. Shallow defects include shallow dirt, shallow scratches, tracks, and the like. The specific detection process is shown in fig. 12:
dividing the obtained conventional image into a plurality of circular rings with stable gray level change according to the gray level distribution of the lens;
continuously dividing the divided circular ring into equally divided circular rings with the difference value of the inner radius and the outer radius as a set value (set according to actual needs);
and calculating the average gray value of the equally divided circular ring, traversing the pixel values on the equally divided circular ring, and judging that the pixel values are shallow defects if the gray value difference exceeds a set threshold value.
The detection method further comprises the step of carrying out ghost elimination operation on the conventional image before defect detection:
carrying out gray stretching on the conventional image to make the gray difference between the lens area and the frosted area equal, and then carrying out affine transformation to move to a ghost area to obtain a transformed image;
subtracting the conventional image before being processed from the transformed image to remove ghost interference:
Mat res ＝Mat src -a*M 0 *Mat src
wherein Mat res Mat for the resulting image src For ghost images, a is the gray scale stretch factor, M 0 Is an affine transformation matrix.
The invention also provides a defect detection method of the second lens. Preferably, the method is used for detecting lenses with diameters of 5-8mm and thicknesses of less than 1mm. Referring to fig. 13, the detection method includes: placing the above lens between the dome light source 4 and the annular light source 5 according to the foregoing embodiment or other embodiments, turning on the coaxial light source 3, the dome light source 4, and the annular light source 5, and turning off the backlight light source 6, taking a regular image;
turning on a backlight source 6, turning off a coaxial light source 3, a dome light source 4 and an annular light source 5, and shooting a back field image;
performing defect detection on the conventional image, and judging whether surface white spots, film defects, dirt and hairline defects exist or not;
and performing defect detection on the back field image, and judging whether a black point defect exists.
Of course, according to the concept of the present invention, when detecting the defect of the conventional image, if the result is that the lens is defective, the detection process can be ended, and the result that the lens is defective is output. And after the defects are detected by the conventional image, whether the black point defects exist or not can be continuously detected, so that the summary statistics of various defect forms of the lens can be carried out, and a foundation is provided for the improvement of the production process.
The defect detection method for the lens with the diameter of 5-8mm and the thickness of less than 1mm can also comprise the detection of shallow defects:
dividing the conventional image and the back field image into a plurality of circular rings with stable gray level change according to the gray level distribution of the lens;
continuously dividing the divided circular ring into equal-divided circular rings with the difference value of the inner radius and the outer radius as a set value;
and calculating the average gray value of the equally divided circular ring, traversing the pixel values on the equally divided circular ring, and judging that the pixel values are shallow defects if the gray value difference exceeds a set threshold value.
Furthermore, before defect detection of a conventional image, ghost interference needs to be eliminated:
carrying out gray stretching on the conventional image to make the gray difference between the lens area and the frosted area equal, and then carrying out affine transformation to move to a ghost area to obtain a transformed image;
subtracting the conventional image before being processed from the transformed image to remove ghost interference:
Mat res ＝Mat src -a*M 0 *Mat src
wherein Mat res Mat for the resulting image src For ghost images, a is the gray scale stretch factor, M 0 Is an affine transformation matrix.
The invention also provides a defect detection method of the third lens. Preferably, the detection method is used for detecting the defects of the lens with the diameter of more than or equal to 8mm and the thickness of less than 1mm. Referring to fig. 14, the detection method includes:
the lens is arranged between the dome light source 4 and the annular light source 5 according to the previous embodiment or other embodiments, the coaxial light source 3 and the dome light source 4 are turned on, the annular light source 5 and the backlight light source 6 are turned off, and a bright field image is shot;
turning on the annular light source 5, turning off the coaxial light source 3, the dome light source 4 and the backlight light source 6, and shooting a dark field image;
turning on a backlight source 6, turning off a coaxial light source 3, a dome light source 4 and an annular light source 5, and shooting a back field image;
performing defect detection on the bright field image, and judging whether surface white point defects, film defects, dirt and white point defects exist or not;
detecting defects of the dark field image, and judging whether scratch, hairline and road type defects exist or not;
and performing defect detection on the back field image, and judging whether a black point defect exists.
Similarly, before defect detection is performed on bright field images and dark field images, ghost interference needs to be eliminated:
gray stretching is carried out on the bright field image and the dark field image, so that gray difference values of the lens area and the frosted area are equal, affine transformation is carried out, and then the lens area and the frosted area are moved to a ghost area, and a transformed image is obtained;
subtracting the bright field image and the dark field image before being processed from the respective transformed images respectively to remove ghost interference:
Mat res ＝Mat src -a*M 0 *Mat src
wherein Mat res Mat for the resulting image src For ghost images, a is the gray scale stretch factor, M 0 Is an affine transformation matrix.
In addition, for lenses with diameters of more than or equal to 8mm and thicknesses of less than 1mm, the detection of bright field images, dark field images and back field images can also comprise shallow defect detection:
dividing the bright field image, the dark field image and the back field image into a plurality of rings with stable gray level change according to the gray level distribution of the lens;
continuously dividing the divided circular ring into equal-divided circular rings with the difference value of the inner radius and the outer radius as a set value;
and calculating the average gray value of the equally divided circular ring, traversing the pixel values on the equally divided circular ring, and judging that the pixel values are shallow defects if the gray value difference exceeds a set threshold value.
In addition, the defect detection for the lens with the diameter of more than or equal to 8mm and the thickness of less than 1mm further comprises the step of demolding defect detection so as to distinguish white spot defects and demolding defects:
multiplying the bright field image and the dark field image by a set coefficient to obtain a differential image:
Mat sub ＝a*Mat L -b*Mat D
wherein: mat (Mat) L Mat for bright field image D For dark field images, a and b are scale factors, mat sub Is the difference image.
| Defect type | Bright field image | Dark field image | Back field image |
| White point | Imaging system | Imaging system | Nonimaging |
| Stripping film | Imaging system | Nonimaging | Nonimaging |
TABLE 1
The principle of obtaining a differential image for detecting the demolding defect is as follows, with reference to table 1 and fig. 15 to 17: the white spot defect and the demolding defect have different imaging effects under different illumination conditions. The release defect is only imaged on the bright field image and cannot be distinguished from the white spot. It is necessary to perform the processing again on the basis of the acquired image. Because the white point is imaged in both the bright field image and the dark field image, the imaging effect of the white point is weakened without influencing the imaging effect of the demolding after the two images are subtracted after being multiplied by corresponding coefficients. Therefore, after the bright field image and the dark field image are obtained, the detection of the defects of the film release can be performed.
The invention also provides a defect detection method of the lens with the lens thickness larger than the depth of field range of the telecentric lens. Referring to FIG. 18, in this embodiment, the defect detection for a lens having a thickness of 1mm or more is performed by the following method:
placing a lens with a thickness of 1mm or more between the dome light source 4 and the annular light source 5 according to the previous embodiment or other embodiments, turning on the coaxial light source 3, the dome light source 4 and the annular light source 5, and turning off the backlight light source 6;
the driving device 25 drives the image sensor 23 and the telecentric lens 24 to move for layer shooting to obtain 2-5 layer shooting images;
and preprocessing, detecting region segmentation and BLOB analysis are sequentially carried out on the obtained photographed images of each layer, and defect judgment is carried out according to the set defect standard parameters.
According to the inventive concept, defect detection of a layer shot image may also include shallow defect detection:
dividing each layer of photographed image into a plurality of rings with stable gray level change according to the gray level distribution of the lens;
continuously dividing the divided circular ring into equal-divided circular rings with the difference value of the inner radius and the outer radius as a set value;
and calculating the average gray value of the equally divided circular ring, traversing the pixel values on the equally divided circular ring, and judging that the pixel values are shallow defects if the gray value difference exceeds a set threshold value.
Likewise, for layer imaging, ghost interference elimination operations may be performed prior to defect detection:
carrying out gray stretching on each layer of photographed image to make the gray difference value between the lens area and the frosted area equal, and then carrying out affine transformation to move to a ghost area to obtain a transformed image;
subtracting the layer shot image before being processed from the transformed image to remove ghost interference:
Mat res ＝Mat src -a*M 0 *Mat src
wherein Mat res Mat for the resulting image src For ghost images, a is the gray scale stretch factor, M 0 Is an affine transformation matrix.
It should be noted that the methods of the present invention are not limited to defect detection of lenses of corresponding dimensions, but may be used to detect defects of lenses of other dimensions. That is, the embodiments mentioned herein are not limited to the dimensions used, and the measurement modes selected correspond to different measurement accuracies.
The lens defect detection system and the detection method can use different light source combination schemes according to the defect type, and are high in detection accuracy and wide in application range. The detection method provided by the invention comprises the steps of eliminating ghost interference on bright field images, dark field images and conventional images, so that the defect exposure is obvious, the detection accuracy is improved, and the omission ratio is reduced. The detection method further comprises the step of obtaining a differential image through the bright field image and the dark field image so as to effectively distinguish white point defects and demoulding defects, improve the detection capability and reduce the omission ratio. The detection method also comprises a shallow defect detection method, wherein shallow defects are segmented by analyzing the relative change of the gray value of the local area of the lens, so that the detection sensitivity is improved, and the omission ratio is reduced.
The lens defect detection system and the detection method of the invention have no limitation on the detection target, and can be, for example, an aspheric lens, a spherical lens or a periscope type mobile phone lens.
The above description is only one embodiment of the present invention and is not intended to limit the present invention, and various modifications and variations of the present invention will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (12)
1. A lens defect detection method using a lens defect detection system, characterized in that the lens defect detection system comprises a lens, an imaging unit (2), a coaxial light source (3), a dome light source (4), an annular light source (5) and a backlight light source (6) which are sequentially arranged, wherein the imaging unit (2), the coaxial light source (3), the dome light source (4), the annular light source (5) and the backlight light source (6) are coaxially arranged, and the dome light source (4) and the annular light source (5) are alternately arranged; the image pickup unit (2) comprises a supporting plate (21), a fixed plate (22) arranged on the supporting plate (21), an image sensor (23) coaxially arranged on the fixed plate (22) in sequence, a telecentric lens (24) and a driving device (25) for driving the fixed plate (22) to move;
the detection method comprises the following steps:
placing a lens between the dome light source (4) and the annular light source (5), turning on the coaxial light source (3) and the dome light source (4), and turning off the annular light source (5) and the backlight light source (6) to shoot a bright field image;
turning on the annular light source (5), and turning off the coaxial light source (3), the dome light source (4) and the backlight light source (6), so as to shoot a dark field image;
turning on the backlight source (6), turning off the coaxial light source (3), the dome light source (4) and the annular light source (5), and shooting a back field image;
performing defect detection on the bright field image, and judging whether defects of demolding, film shortage, dirt and white spots exist or not;
performing defect detection on the dark field image, and judging whether white spots, scratches and hairlines exist or not;
performing defect detection on the back field image, and judging whether a black point defect exists or not;
distinguishing white point defects and demolding defects based on the bright field image, the dark field image and the back field image;
the defect detection further comprises the specific steps of detecting whether shallow defects exist or not: dividing an image into a plurality of circular rings with stable gray level change according to the gray level distribution of a lens; continuously dividing the divided circular ring into equal-divided circular rings with the difference value of the inner radius and the outer radius as a set value; calculating the average gray value of the equally divided circular ring, traversing the pixel values on the equally divided circular ring, and judging that the pixel values are shallow defects if the gray value difference exceeds a set threshold value;
the specific steps for distinguishing white spot defects from demolding defects include:
multiplying the bright field image and the dark field image by a set coefficient to obtain a differential image:；
wherein: mat (Mat) L Mat for bright field image D For dark field images, a and b are scale factors, mat sub For the difference image;
the principle of obtaining a differential image for demolding defect detection is as follows: the imaging effect of the white point defect and the imaging effect of the demoulding defect under different illumination conditions are different, the demoulding defect only forms an image on a bright field image and cannot be distinguished from the white point, the white point is required to be processed again on the basis of the obtained image, the white point is imaged on the bright field image and the dark field image, the white point imaging effect is weakened after the two images are subtracted after being multiplied by corresponding coefficients, the imaging effect of the demoulding is not influenced, and the demoulding defect detection is carried out after the bright field image and the dark field image are obtained;
wherein the shallow defect comprises one or more of shallow dirt, shallow scratch and track.
2. The lens defect detection method according to claim 1, characterized in that a connection plate (41) is provided on the dome light source (4), and the coaxial light source (3) is fixedly supported on the connection plate (41).
3. The lens defect detection method according to claim 1, wherein the backlight light source (6) comprises a diffusion plate (61), the color of the diffusion plate (61) and the light source band colors of the coaxial light source (3), dome light source (4) and ring light source (5) being set to complementary colors.
4. The lens defect detection method according to claim 1, wherein the backlight light source (6) includes a diffusion plate (61), and the diffusion plate (61) is made of a black translucent material.
5. A lens defect detection method according to claim 3, characterized in that the surface roughness of the diffusion plate (61) is 3.2-25 Ra, and the absorptivity of the diffusion plate (61) to the optical system light source band is 70-95%.
6. A lens defect detection method according to claim 3, characterized in that the backlight source (6) further comprises backlight beads, the diffusion plate (61) is placed between the backlight beads and the light emitting surface of the annular light source (5), and the distance between the diffusion plate and the backlight beads is > 10mm.
7. The method of any one of claims 1-6, further comprising ghost elimination of the bright field image and dark field image prior to defect detection: gray stretching is carried out on the bright field image and the dark field image to enable gray difference values of a lens area and a frosted area to be equal, affine transformation is carried out to move to a ghost area, and a transformed image is obtained;
subtracting the bright field image and the dark field image before being processed from the respective transformed images to remove ghost interference:
；
wherein Mat res Mat for the resulting image src For ghost images, a is the gray scale stretch factor, M 0 Is an affine transformation matrix.
8. The method of claim 1, wherein the lens has a thickness of less than 1mm.
9. The lens defect detection method of claim 1, when the thickness of the lens is greater than the depth of field of the telecentric lens (24), further comprising:
placing a lens between the dome light source (4) and the annular light source (5), turning on the coaxial light source (3), the dome light source (4) and the annular light source (5), and turning off the backlight light source (6);
the driving device (25) drives the image sensor (23) and the telecentric lens (24) to move for layer shooting to obtain 2-5 layer shooting images;
and performing defect detection on the obtained photographed images of each layer.
10. The method of claim 9, wherein the defect detection of the layer shot image comprises shallow defect detection:
dividing each layer of photographed image into a plurality of rings with stable gray level change according to the gray level distribution of the lens;
continuously dividing the divided circular ring into equal-divided circular rings with the difference value of the inner radius and the outer radius as a set value;
and calculating the average gray value of the equally divided circular ring, traversing the pixel values on the equally divided circular ring, and judging that the pixel values are shallow defects if the gray value difference exceeds a set threshold value.
11. The method of claim 9 or 10, wherein the imaging further comprises eliminating ghosting prior to defect detection:
carrying out gray stretching on each layer of photographed image to make gray difference values of the lens area and the frosted area equal, and then carrying out affine transformation to move to a ghost area to obtain a transformed image;
subtracting the layer shot image before being processed from the transformed image to remove ghost interference:
wherein Mat res Mat for the resulting image src For ghost images, a isCoefficient of gray scale stretching, M 0 Is an affine transformation matrix.
12. The method of claim 9, wherein the lens has a thickness of 1mm or more.
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| CN114113113A (en) * | 2021-11-29 | 2022-03-01 | 哈尔滨工业大学 | Three-light-source microscope system device for positioning and identifying surface micro-defects |
| CN114136987B (en) * | 2021-12-03 | 2024-04-30 | 中科计算技术西部研究院 | Device and method for detecting deformation defect of lens |
| CN114113129B (en) * | 2021-12-03 | 2024-04-30 | 中科计算技术西部研究院 | Lens micro defect recognition and grabbing system and method |
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