CN117495842A - Panel color leakage process defect detection method, system, equipment and medium - Google Patents
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Abstract
The invention provides a method, a system, equipment and a medium for detecting panel color missing process defects, which relate to the technical field of panel missing process defect detection and comprise the following steps: acquiring a matching template based on an original panel image, wherein the matching template comprises all color units; performing similarity matching on the panel images to be detected based on the matching templates to obtain a plurality of candidate templates; and acquiring rectangular areas corresponding to all the color units based on the candidate templates, and comparing color differences based on the rectangular areas to judge whether color leakage processing defects exist or not. The invention combines the template matching method and the color difference analysis mode, solves the problems that the CF color filter has few identifying characteristics of the missing processing defects and the target detection algorithm is difficult to effectively detect, and realizes the effective detection of the CF missing processing defects.
Description
Technical Field
The invention relates to the technical field of panel leakage process defect detection, in particular to a panel color leakage process defect detection method, system, equipment and medium.
Background
CF color filters are an important component of a panel lcd product, and the display can exhibit colorful colors, mainly depending on the function of the CF color filters. The CF color filter is formed by repeating a periodic arrangement of three basic color units of RGB.
In the CF color filter production process, a situation that a certain color process is missed may occur, which is called missing process, which is a serious defect, and the subsequent process is reprocessed on the basis of missing one process, so that the produced product becomes waste and wastes the productivity of the subsequent process. Therefore, the panel factory can strictly control the missing process defects, the factory photographs the produced panel products through an automatic optical inspection machine (AOI), then the manual naked eyes judge the pictures, whether the missing process defects exist in the pictures is identified, and after the missing process defects are found, the panel products are transported to a repair machine for reworking of the missing process.
However, the number of pictures produced by the panel product in the production process is more than tens of thousands, more manpower is required for judging the pictures, more manpower cost is required, the manpower is influenced by the experience enrichment degree and the state, and the misjudgment rate is generally higher. Therefore, panel factories generally start to introduce a system based on an automatic graph judgment algorithm to replace a manual graph judgment, the system generally adopts a target detection algorithm as a core detection algorithm, but the algorithm generally has a good detection effect on defects such as foreign matters falling on products, the missing processing defects have no foreign matter characteristics, the missed processing part is not different from a normal background, and the general target detection algorithm is difficult to realize effective detection.
Disclosure of Invention
The invention provides a method, a system, equipment and a medium for detecting panel color leakage processing defects, which aim to solve the problem that the defect of the CF color filter leakage processing is difficult to identify by a target detection algorithm.
In a first aspect, an embodiment of the present invention provides a method for detecting a defect in a panel color leakage process, where the method includes the following steps:
acquiring a matching template based on an original panel image, wherein the matching template comprises all color units;
performing similarity matching on the panel images to be detected based on the matching templates to obtain a plurality of candidate templates;
and acquiring rectangular areas corresponding to all the color units based on the candidate templates, and comparing color differences based on the rectangular areas to judge whether color leakage processing defects exist or not.
In the above embodiment, the present invention firstly obtains a matching template including RGB three color units, then obtains a plurality of images having the same size as the matching template through the panel image to be detected, and selects an image similar to or the same as the matching template image through a similarity matching manner; and finally, selecting rectangular areas corresponding to the RGB three color units from similar or identical images, judging whether the color difference of any two rectangular areas is larger than a preset value, if the color difference is smaller, indicating that the color of any two rectangular areas is similar, and if the color difference is similar, the color leakage processing defect exists in one area, and transporting the panel product to a repairing machine for reworking of the leakage processing.
As some optional embodiments of the present application, the procedure for obtaining the matching template based on the original panel image is as follows:
performing image interception processing on the original panel image to obtain an initial matching template; the initial matching template comprises three RGB color units;
and carrying out edge contour extraction processing on the initial matching template to obtain a final matching template.
In the above embodiment, the gray-scale pattern is generally adopted for matching, but because of the large difference of the collected background colors of the images caused by the difference of the debugging of the automatic optical inspection machine (AOI) light source, the gray-scale pattern is directly used as the pattern, so that the risk of missing matching is large, if the gray-scale pattern is adopted for matching, each color needs to be maintained for one pattern, the maintenance cost is too high, and the matching time cost is higher during the pattern matching, so that the matching pattern needs to be converted from the color pattern of three channels into a single-channel pattern; that is, the truncated matching template is first converted into a gray-scale map, and then the edge contour extraction process (using the canny algorithm) is performed on the initial matching template to obtain the final matching template.
As some optional embodiments of the present application, the process of performing similarity matching on a panel image to be detected based on a matching template is as follows:
performing edge contour extraction processing on the panel picture to be detected, taking the upper left corner pixel point of the panel picture to be detected as an upper left corner point coordinate, and taking the upper left corner point coordinate as a reference point to obtain an initial candidate template;
sequentially shifting the initial candidate templates rightward/upward by one pixel to obtain a plurality of candidate templates;
and sequentially calculating the similarity between the candidate templates and the matching templates, and if the similarity is larger than a matching threshold, matching the corresponding candidate templates with the matching templates to obtain the final candidate templates.
In the above embodiment, an initial candidate template is first obtained by coordinate positioning, and then several templates with the same size as the candidate template can be obtained by translation, so as to facilitate the similarity matching of the templates in the later stage.
As some optional embodiments of the present application, the similarity uses a cosine similarity calculation method, a hash calculation method, a histogram calculation method, or a pearson correlation coefficient calculation.
In the above embodiment, by selecting a suitable similarity calculation manner, a candidate template similar to the matching template can be quickly obtained, so as to facilitate the subsequent color difference verification processing on the similar candidate template.
As some optional embodiments of the present application, the procedure of obtaining rectangular areas corresponding to all color units based on the candidate templates is as follows:
dividing the final matching template into three color unit areas;
and respectively cutting out a rectangular area from the three color unit areas to obtain a first rectangular area, a second rectangular area and a third rectangular area corresponding to the three color unit areas.
In the above embodiment, by cutting out small areas among the three color areas, the calculation difficulty of the later color difference comparison can be reduced.
As some optional embodiments of the present application, the procedure for performing color difference comparison based on rectangular areas is as follows:
extracting color values of RGB three-color channels from the first rectangular area, the second rectangular area and the third rectangular area, and calculating the value average value of each channel under three rectangular coordinates;
calculating the chromatic aberration of any two rectangular areas in the three color unit areas based on the value average value of each channel under the rectangular coordinates;
if the color difference of any two rectangular areas is smaller than the color difference threshold value, judging that the panel to be detected has color omission defect.
In the above embodiment, by determining whether the color difference between any two rectangular areas is greater than a preset value, if the color difference is less than the preset value, it is indicated that the color of any two rectangular areas is similar, and if one of the two rectangular areas has a color missing processing defect, the panel product needs to be transported to a repair machine for reworking of missing processing.
As some optional embodiments of the present application, the calculation formula of the color difference of any two rectangular areas is as follows:
wherein p' r And p r Respectively represent the value average value, p 'of the colors of any two rectangular areas on the R channel' g And p g Respectively represent the value average value, p 'of colors of any two rectangular areas on the G channel' b And p b The average value of the colors of any two rectangular areas on the B channel is respectively shown.
In the above embodiment, the color difference of any two rectangular areas is calculated by the euclidean distance, so that the color leakage processing defect can be rapidly detected.
In a second aspect, the present invention provides a panel color leakage process defect detection system, the system comprising:
a template acquisition unit that acquires a matching template based on an original panel image, the matching template including all color units;
the similarity matching unit is used for performing similarity matching on the panel image to be detected based on the matching template so as to obtain a plurality of candidate templates;
and the color difference matching unit acquires rectangular areas corresponding to all the color units based on the candidate templates, and performs color difference comparison based on the rectangular areas to judge whether color leakage processing defects exist or not.
In a third aspect, the present invention provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor implementing the panel color omission process defect detection method when executing the computer program.
In a fourth aspect, the present invention provides a computer readable storage medium having a computer program stored thereon, which when executed by a processor implements the panel color leakage process defect detection method.
The beneficial effects of the invention are as follows:
the invention combines the template matching method and the color difference analysis mode, solves the problems that the CF color filter has few identifying characteristics of the missing processing defects and the target detection algorithm is difficult to effectively detect, and realizes the effective detection of the CF missing processing defects.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of a computer device in a hardware operating environment according to an embodiment of the present invention;
FIG. 2 is a diagram showing steps of a method for detecting defects in a panel color leakage process according to an embodiment of the present invention;
FIG. 3 is a schematic illustration of an original panel image according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a matching template according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of a rectangular area color difference analysis according to an embodiment of the present invention;
FIG. 6 is a system block diagram of a panel color leakage process defect detection system according to an embodiment of the invention.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.
In order to solve the problem that the defect of the CF color filter leakage process is difficult to identify by the target detection algorithm. The application provides a method, a system, equipment and a medium for detecting defects of panel color leakage processing, and before introducing a specific technical scheme of the application, a hardware operation environment related to the scheme of the embodiment of the application is introduced.
Referring to fig. 1, fig. 1 is a schematic structural diagram of a computer device in a hardware running environment according to an embodiment of the present application.
As shown in fig. 1, the computer device may include: a processor, such as a central processing unit (Central Processing Unit, CPU), a communication bus, a user interface, a network interface, a memory. Wherein the communication bus is used to enable connection communication between these components. The user interface may comprise a Display, an input unit such as a Keyboard (Keyboard) and optionally a standard wired interface, a wireless interface. The network interface may optionally include a standard wired interface, a wireless interface (e.g., a wireless fidelity interface). The Memory may be a high-speed random access Memory (RandomAccess Memory, RAM) Memory, a stable Non-Volatile Memory (NVM), such as a disk Memory, or alternatively may be a storage device independent of the aforementioned processor.
Those skilled in the art will appreciate that the architecture shown in fig. 1 is not limiting of a computer device and may include more or fewer components than shown, or may combine certain components, or a different arrangement of components.
As shown in fig. 1, an operating system, a data storage module, a network communication module, a user interface module, and a storage module of a software program may be included in a memory as one type of storage medium.
In the computer device shown in fig. 1, the network interface is mainly used for data communication with the network server; the user interface is mainly used for carrying out data interaction with a user; the processor and the memory in the computer equipment can be arranged in the computer equipment, and the computer equipment calls the panel color missing processing defect detection system stored in the memory through the processor and executes the panel color missing processing defect detection method provided by the embodiment of the application.
Based on the hardware environment of the foregoing embodiments, an embodiment of the present application provides a method for detecting a panel color leakage process defect, refer to fig. 2, and fig. 2 is a flowchart of the method for detecting a panel color leakage process defect, where the method flow is as follows:
(1) Acquiring a matching template based on an original panel image, wherein the matching template comprises all color units; the original panel image is a panel inspection image obtained by an automatic optical inspection machine (AOI), preferably, the original panel image is an image without color leakage process defect, please refer to fig. 3, and fig. 3 is a schematic diagram of the original panel image.
Specifically, the procedure for obtaining the matching template based on the original panel image is as follows:
(1.1) performing image interception processing on an original panel image to obtain an initial matching template; wherein the initial matching template at least comprises three RGB color units;
(1.2) the general template matching is carried out by adopting a gray-scale image, but because of the large difference of the background colors of the acquired images caused by the difference of the debugging of an automatic optical inspection machine (AOI) light source, the gray-scale image is directly used as the template, so that the risk of missed matching exists, if the gray-scale image is adopted for matching, one template is required to be maintained for each color, the maintenance cost is too high, and the matching time cost is higher when the templates are matched, so that the matching template is required to be converted from a three-channel color image to a single-channel image; that is, the truncated matching template is first converted into a gray-scale image, and then the edge contour extraction process (using the canny algorithm) is performed on the initial matching template to obtain the final matching template, please refer to fig. 4, fig. 4 is a schematic diagram of the matching template, and the width and height of the matching template are denoted as w and h.
(2) Performing similarity matching on the panel images to be detected based on the matching templates to obtain a plurality of candidate templates;
specifically, the process of performing similarity matching on the panel image to be detected based on the matching template is as follows:
(2.1) firstly carrying out edge contour extraction processing (using a canny algorithm) on a panel picture to be detected, taking the upper left corner pixel point of the panel picture to be detected as an upper left corner point coordinate, namely starting point coordinates (0, 0), taking the upper left corner point coordinate as a reference point, and obtaining a candidate template with the same size as a matching template, namely, representing the first candidate template coordinate as [0, w,0, h ]; meanwhile, the lower left corner pixel point, the upper right corner pixel point and the lower right corner pixel point of the panel picture to be detected can be used as corresponding starting point coordinates, which are not limited by the embodiment of the invention.
(2.2) sequentially shifting the candidate templates rightward/upward by one pixel to obtain a plurality of candidate templates having the same size as the matching template, and assuming that the upper left corner coordinates of the current candidate template are (x, y), the current candidate template coordinates are represented as [ x, y, x+w, y+h ].
(2.3) sequentially calculating the similarity between a plurality of candidate templates and the matching template, if the similarity is larger than a matching threshold, matching the corresponding candidate templates with the matching template, and selecting the candidate template matched with the matching template as a final candidate template, so that one or more candidate templates similar to the matching template can be obtained; specifically, the matching degree threshold is a preset value, and may be set according to actual situations.
Specifically, the similarity is calculated by adopting a cosine similarity calculation method, a hash calculation method, a histogram calculation method or a pearson correlation coefficient; preferably, the cosine similarity calculation method is adopted to obtain the similarity between the candidate template and the matching template, the value range of the similarity is between 0 and 1, and the higher the matching degree is, the closer the similarity is to 1.
(3) Acquiring rectangular areas corresponding to all the color units based on the candidate templates, and comparing color differences based on the rectangular areas to judge whether color leakage processing defects exist or not;
specifically, the procedure for obtaining rectangular areas corresponding to all color units based on the candidate templates is as follows:
(3.1) dividing the final matching template into three color cell regions, i.e. obtaining three rectangular regions on one or more candidate templates, respectively, see fig. 5.
(3.2) cutting out one rectangular region from the three color cell regions respectively to obtain a first rectangular region, a second rectangular region and a third rectangular region corresponding to the three color cell regions, wherein the first rectangular region, the second rectangular region and the third rectangular region are respectively denoted as [ x ] 11 ,y 11 ,x 12 ,y 12 ],[x 21 ,y 21 ,x 22 ,y 22 ],[x 31 ,y 31 ,x 32 ,y 32 ]。
Specifically, the procedure for color difference comparison based on rectangular areas is as follows:
(3.3) extracting the colors of the RGB three-color channels from the first rectangular region, the second rectangular region and the third rectangular region, calculating the average value of the color values of each channel under three rectangular coordinates, and respectively recording as p1 r ,p1 g ,p1 b ,p2 r ,p2 g ,p2 b ,p3 r ,p3 g ,p3 b 。
And (3.4) calculating the chromatic aberration of any two rectangular areas in the three color unit areas based on the value average value of each channel under the rectangular coordinates, for example, the chromatic aberration of the first rectangular area and the second rectangular area is marked as diff_12, and the marked chromatic aberration diff_13 of the first rectangular area and the third rectangular area and the marked chromatic aberration diff_23 of the second rectangular area and the third rectangular area are similarly marked.
And (3.5) if the color difference of any two rectangular areas is smaller than a color difference threshold, judging that the panel to be detected has color missing defect, wherein the color difference threshold is a preset value, and when the calculated color difference between any two rectangular areas is smaller than the color difference threshold, judging that the picture has color missing defect, wherein the matching degree threshold is a preset value and can be set according to actual conditions, if the color difference calculated between any two rectangular areas is smaller than the color difference threshold, judging that the two color units are consistent.
Specifically, the calculation formula of the color difference of any two rectangular areas is as follows:
wherein p' r And p r Respectively represent the value average value, p 'of the colors of any two rectangular areas on the R channel' g And p g Respectively represent the value average value, p 'of colors of any two rectangular areas on the G channel' b And p b Respectively representing the value average value of colors of any two rectangular areas on the B channel; for example, for the first rectangular region and the second rectangular region, the color difference is noted as:
similarly, the color difference diff_13 and the color difference diff_23 can be obtained through the formulas, namely, the color difference of any two rectangular areas is calculated through the Euclidean distance, and the color leakage processing defect can be rapidly detected.
In summary, the invention firstly obtains a matching template containing RGB three color units, then obtains a plurality of images with the same size as the matching template through the panel image to be detected, and selects the images similar to or the same as the matching template image through a similarity matching mode; finally, selecting rectangular areas corresponding to RGB three color units from similar or same images, judging whether the color difference of any two rectangular areas is larger than a preset value, if the color difference is smaller, indicating that the color of any two rectangular areas is similar, and if the color difference is similar, a certain area has a color leakage processing defect, and transporting a panel product to a repairing machine for reworking of leakage processing; the method solves the problems that the CF color filter has few identifying characteristics of missing processing defects and the target detection algorithm is difficult to effectively detect by combining a template matching method and a color difference analysis mode, and realizes the effective detection of the CF missing processing defects.
In addition, in an embodiment, based on the same inventive concept as the previous embodiment, the embodiment of the present invention provides a panel color leakage process defect detection system, which corresponds to the method of embodiment 1 one by one, please refer to fig. 6, fig. 6 is a block diagram of the panel color leakage process defect detection system, the system includes:
a template acquisition unit that acquires a matching template based on an original panel image, the matching template including all color units;
the similarity matching unit is used for performing similarity matching on the panel image to be detected based on the matching template so as to obtain a plurality of candidate templates;
and the color difference matching unit acquires rectangular areas corresponding to all the color units based on the candidate templates, and performs color difference comparison based on the rectangular areas to judge whether color leakage processing defects exist or not.
It should be noted that, each unit in the panel color missing process defect detection system in this embodiment corresponds to each step in the panel color missing process defect detection method in the foregoing embodiment, so the specific implementation manner and the achieved technical effect of this embodiment may refer to the implementation manner of the foregoing panel color missing process defect detection method, and will not be described herein again.
Furthermore, in an embodiment, the present application also provides a computer device, which includes a processor, a memory, and a computer program stored in the memory, which when executed by the processor, implements the method in the foregoing embodiment.
Furthermore, in an embodiment, the present application also provides a computer storage medium, on which a computer program is stored, which when being executed by a processor, implements the method in the foregoing embodiment.
In some embodiments, the computer readable storage medium may be FRAM, ROM, PROM, EPROM, EEPROM, flash memory, magnetic surface memory, optical disk, or CD-ROM; but may be a variety of devices including one or any combination of the above memories. The computer may be a variety of computing devices including smart terminals and servers.
In some embodiments, the executable instructions may be in the form of programs, software modules, scripts, or code, written in any form of programming language (including compiled or interpreted languages, or declarative or procedural languages), and they may be deployed in any form, including as stand-alone programs or as modules, components, subroutines, or other units suitable for use in a computing environment.
As an example, the executable instructions may, but need not, correspond to files in a file system, may be stored as part of a file that holds other programs or data, for example, in one or more scripts in a hypertext markup language (HTML, hyper Text Markup Language) document, in a single file dedicated to the program in question, or in multiple coordinated files (e.g., files that store one or more modules, sub-programs, or portions of code).
As an example, executable instructions may be deployed to be executed on one computing device or on multiple computing devices located at one site or, alternatively, distributed across multiple sites and interconnected by a communication network.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. read-only memory/random-access memory, magnetic disk, optical disk), comprising several instructions for causing a multimedia terminal device (which may be a mobile phone, a computer, a television receiver, or a network device, etc.) to perform the method described in the embodiments of the present application.
The foregoing description is only of the preferred embodiments of the present application, and is not intended to limit the scope of the claims, and all equivalent structures or equivalent processes using the descriptions and drawings of the present application, or direct or indirect application in other related technical fields are included in the scope of the claims of the present application.
Claims (10)
1. A method for detecting defects of panel color leakage process is characterized in that the method comprises the following steps:
acquiring a matching template based on an original panel image, wherein the matching template comprises all color units;
performing similarity matching on the panel images to be detected based on the matching templates to obtain a plurality of candidate templates;
and acquiring rectangular areas corresponding to all the color units based on the candidate templates, and comparing color differences based on the rectangular areas to judge whether color leakage processing defects exist or not.
2. The method for detecting defects in a panel color leakage process according to claim 1, wherein the process of obtaining the matching template based on the original panel image is as follows:
performing image interception processing on the original panel image to obtain an initial matching template; the initial matching template comprises three RGB color units;
and carrying out edge contour extraction processing on the initial matching template to obtain a final matching template.
3. The method for detecting defects in a panel color leakage process according to claim 1, wherein the process of similarity matching of the panel image to be detected based on the matching template is as follows:
performing edge contour extraction processing on the panel picture to be detected, taking the upper left corner pixel point of the panel picture to be detected as an upper left corner point coordinate, and taking the upper left corner point coordinate as a reference point to obtain a candidate template with the same size as the matching template;
sequentially shifting the candidate templates rightward/upward by one pixel to obtain a plurality of candidate templates;
and sequentially calculating the similarity between the candidate templates and the matching templates, and if the similarity is larger than a matching threshold, matching the corresponding candidate templates with the matching templates to obtain the final candidate templates.
4. A panel color leakage process defect detection method according to claim 3, wherein the similarity is calculated by cosine similarity calculation method, hash calculation method, histogram calculation method or pearson correlation coefficient.
5. The method for detecting a panel color leakage process defect according to claim 4, wherein the process of obtaining rectangular areas corresponding to all color units based on the candidate templates is as follows:
dividing the final matching template into three color unit areas;
and respectively cutting out a rectangular area from the three color unit areas to obtain a first rectangular area, a second rectangular area and a third rectangular area corresponding to the three color unit areas.
6. The method for detecting a panel color leakage process defect according to claim 5, wherein the process of performing color difference comparison based on the rectangular area is as follows:
extracting color values of RGB three-color channels from the first rectangular area, the second rectangular area and the third rectangular area, and calculating the value average value of each channel under three rectangular coordinates;
calculating the chromatic aberration of any two rectangular areas in the three color unit areas based on the value average value of each channel under the rectangular coordinates;
if the color difference of any two rectangular areas is smaller than the color difference threshold value, judging that the panel to be detected has color omission defect.
7. The method for detecting a panel color leakage process defect according to claim 6, wherein the color difference between any two rectangular areas is calculated as follows:
wherein p' r And p r Respectively represent the value average value, p 'of the colors of any two rectangular areas on the R channel' g And p g Respectively represent the value average value, p 'of colors of any two rectangular areas on the G channel' b And p b The average value of the colors of any two rectangular areas on the B channel is respectively shown.
8. A panel color leakage process defect detection system, the system comprising:
a template acquisition unit that acquires a matching template based on an original panel image, the matching template including all color units;
the similarity matching unit is used for performing similarity matching on the panel image to be detected based on the matching template so as to obtain a plurality of candidate templates;
and the color difference matching unit acquires rectangular areas corresponding to all the color units based on the candidate templates, and performs color difference comparison based on the rectangular areas to judge whether color leakage processing defects exist or not.
9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized by: the processor, when executing a computer program, implements a panel color leakage process defect detection method as defined in any one of claims 1-7.
10. A computer readable storage medium, wherein a computer program is stored on the computer readable storage medium, the computer program when executed by a processor implementing a panel color omission process defect detection method according to any one of claims 1-7.
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