Micro-display device circuit area defect detection method and device and storage medium

Abstract

The invention discloses a micro-display device circuit area defect detection method and device and a storage medium, which are used for improving the screen body defect detection precision of a display screen image containing a circuit area. Shooting a to-be-tested display screen through a flying camera, and collecting a circuit area image of the to-be-tested display screen; copying the circuit area image to generate a first circuit area image and a second circuit area image; performing gray scale expansion processing on the first circuit area image to generate a first template; performing gray scale corrosion processing on the second circuit area image to generate a second template; respectively detecting circuit defect areas of the first template and the second template according to a preset circuit area sample limiting image to generate a circuit dark defect area and a circuit bright defect area; and performing defect identification detection on the circuit dark defect area and the circuit bright defect area to generate circuit area defect data.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of display screen detection, and in particular, to a method, device and storage medium for detecting defects in a circuit area of ​​a micro display device. Background Art

[0002] With the rapid development of industrial and Internet technologies, the industry's requirements for industrial product quality are becoming more and more refined and standardized. As far as the display panel industry is concerned, the quality of products directly affects its product competitiveness. Among them, the accuracy of product shape and size specifications is the most basic process indicator of product quality. As one of the display components of the device, the display screen is used in various high-end devices, such as mobile phones, TVs, tablets, etc. As people's requirements for screen display continue to increase, the display screen has gradually become a technologically sophisticated product.

[0003] Display screen defect detection is a necessary process for adjustment. Display screen defects can be divided into display defects and screen body defects. Display defects refer to the discordant areas that appear when the display screen displays the picture. In the prior art, display defects usually require inputting a specific picture on the display screen to be tested, and then collecting the picture through the camera, and then performing image detection to analyze it. Screen body defects refer to the areas on the surface or inside of the display screen itself that have damage (such as chipped corners, foreign matter, etc.). This type of defect does not require inputting an image, and can be analyzed by collecting the picture with the camera and then performing image detection.

[0004] However, as the application fields of display screens become more and more extensive, more and more functions are added, and sophisticated circuit structures are added inside or on the surface of the display screen. This type of structure will not have much impact on the detection of display defects, because the display screen layer is usually located on the circuit structure. However, since screen defects do not require screen display, and the circuit structure is usually a very thin circuit board, due to the complex internal structure of the circuit structure, it mainly presents blocks with different levels, and the overall area is large, concentrated distribution, and arranged inside the display screen. This type of display screen containing circuit structure is prone to false detection and missed detection of screen defects in the corresponding circuit structure area, which reduces the accuracy of screen defect detection in the circuit area. Summary of the invention

[0005] The present application discloses a method, device and storage medium for detecting defects in a circuit area of ​​a micro display device, which are used to improve the accuracy of detecting defects in a display screen image containing a circuit area.

[0006] The first aspect of the present application discloses a method for detecting defects in a circuit area of ​​a micro display device, comprising: The display screen to be tested is photographed by a flying camera to collect the circuit area image of the display screen to be tested; Copying the circuit area image to generate a first circuit area image and a second circuit area image; Performing grayscale expansion processing on the first circuit area image to generate a first template; Performing grayscale corrosion processing on the second circuit area image to generate a second template; According to the preset circuit area limit sample diagram, the first template and the second template are respectively used to detect the circuit defect area, and a circuit dark defect area and a circuit bright defect area are generated; Defect identification and detection are performed on the dark defect area and the bright defect area of ​​the circuit to generate circuit area defect data.

[0007] Optionally, detecting the circuit defect area of ​​the first template and the second template respectively according to the preset circuit area limit sample diagram to generate the circuit dark defect area and the circuit bright defect area includes: Obtaining dark defect compensation values ​​and bright defect compensation values; Perform pixel-by-pixel segmentation according to a preset dark defect threshold lower limit, dark defect threshold upper limit, circuit area limit sample map, first template and dark defect compensation value to generate a circuit dark defect area; According to the preset lower limit of the bright defect threshold, the upper limit of the bright defect threshold, the circuit area limit sample map, the second template and the bright defect compensation value, pixel-by-pixel segmentation is performed to generate a circuit bright defect area.

[0008] Optionally, dark defect compensation values ​​and bright defect compensation values ​​are obtained, including: The preset circuit area limit sample diagram is copied, and grayscale expansion processing and grayscale corrosion processing are performed respectively to generate a third template and a fourth template; Obtaining grayscale means of the first template, the second template, the third template, and the fourth template to generate a first grayscale mean, a second grayscale mean, a third grayscale mean, and a fourth grayscale mean; Obtaining dark defect grayscale parameters and bright defect grayscale parameters, wherein the dark defect grayscale parameters refer to the pixel grayscale data of each dark defect after grayscale expansion processing, and the bright defect grayscale parameters refer to the pixel grayscale data of each bright defect after grayscale corrosion processing; Generate a dark defect compensation value by using the first grayscale mean, the third grayscale mean and the dark defect grayscale parameter; A bright defect compensation value is generated by the second grayscale mean, the fourth grayscale mean, and the bright defect grayscale parameter.

[0009] Optionally, after photographing the display screen to be tested by using a flying camera to acquire the circuit area image of the display screen to be tested, before copying the circuit area image to generate the first circuit area image and the second circuit area image, the method further includes: The circuit area image is subjected to mean filter noise reduction processing or Gaussian filter noise reduction processing.

[0010] Optionally, before photographing the display screen to be tested by using a flying camera to collect the circuit area image of the display screen to be tested, the method further includes: Capture images of the standard sample limit screen to generate standard images of the product; Generate the initial position of the circuit area and the buffer area on the standard image; The edges of the initial position of the circuit area are detected from the outside to the inside, and all the candidate edge points are screened out according to the preset edge point parameter threshold; Fit all edge candidate points and determine the coordinates of the angle points; Generate a circuit area frame according to the coordinates at the angle point; Crop the standard image according to the circuit area frame to generate a circuit area limited sample image.

[0011] Optionally, defect recognition detection is performed on the dark defect area and the bright defect area of ​​the circuit to generate circuit area defect data, including: Cutting the dark defect area of ​​the circuit of the first template and the bright defect area of ​​the circuit of the second template to generate a dark defect sub-area and a bright defect sub-area; The cut dark defect sub-region and the bright defect sub-region are sent to the classification network for classification to generate classification results; The classification results are used to generate a data list according to the image ID of the display screen image.

[0012] The second aspect of the present application discloses a device for detecting defects in a circuit area of ​​a micro display device, comprising: An acquisition unit is used to photograph the display screen to be tested by using a flying camera to acquire an image of a circuit area of ​​the display screen to be tested; A first generating unit, used for copying the circuit area image to generate a first circuit area image and a second circuit area image; A second generating unit is used to perform grayscale expansion processing on the first circuit area image to generate a first template; A third generating unit is used to perform grayscale corrosion processing on the second circuit area image to generate a second template; A fourth generating unit, configured to detect the circuit defect area of ​​the first template and the second template respectively according to a preset circuit area limit sample diagram, and generate a circuit dark defect area and a circuit bright defect area; The fifth generating unit is used to perform defect recognition detection on the dark defect area and the bright defect area of ​​the circuit to generate circuit area defect data.

[0013] Optionally, the fourth generating unit includes: An acquisition module, used for acquiring a dark defect compensation value and a bright defect compensation value; A first generating module is used to perform pixel-by-pixel segmentation according to a preset dark defect threshold lower limit, a dark defect threshold upper limit, a circuit area limit sample map, a first template and a dark defect compensation value to generate a circuit dark defect area; The second generation module is used to perform pixel-by-pixel segmentation according to a preset bright defect threshold lower limit, a bright defect threshold upper limit, a circuit area limit sample map, a second template and a bright defect compensation value to generate a circuit bright defect area.

[0014] Optionally, obtain modules, including: The preset circuit area limit sample diagram is copied, and grayscale expansion processing and grayscale corrosion processing are performed respectively to generate a third template and a fourth template; Obtaining grayscale means of the first template, the second template, the third template, and the fourth template to generate a first grayscale mean, a second grayscale mean, a third grayscale mean, and a fourth grayscale mean; Obtaining dark defect grayscale parameters and bright defect grayscale parameters, wherein the dark defect grayscale parameters refer to the pixel grayscale data of each dark defect after grayscale expansion processing, and the bright defect grayscale parameters refer to the pixel grayscale data of each bright defect after grayscale corrosion processing; Generate a dark defect compensation value by using the first grayscale mean, the third grayscale mean and the dark defect grayscale parameter; A bright defect compensation value is generated by the second grayscale mean, the fourth grayscale mean, and the bright defect grayscale parameter.

[0015] Optionally, after the collection unit and before the first generation unit, the device further includes: The filtering unit is used to perform mean filtering noise reduction processing or Gaussian filtering noise reduction processing on the circuit area image.

[0016] Optionally, before the collection unit, the device further includes: The sixth generating unit is used to collect images of the standard sample limit screen to generate a standard image of the product; A seventh generating unit, used for generating an initial position of a circuit area and a buffer area on a standard image; A screening unit, used to perform edge detection on the edge of the initial position of the circuit area from the outside to the inside, and screen out all the candidate edge points according to a preset edge point parameter threshold; A determination unit is used to fit all edge candidate points and determine the coordinates of the angle points; An eighth generating unit, used for generating a circuit area frame according to the coordinates at the angle point; The ninth generating unit is used to crop the standard image according to the circuit area frame to generate a circuit area limit sample image.

[0017] Optionally, the fifth generation unit includes: Cutting the dark defect area of ​​the circuit of the first template and the bright defect area of ​​the circuit of the second template to generate a dark defect sub-area and a bright defect sub-area; The cut dark defect sub-region and the bright defect sub-region are sent to the classification network for classification to generate classification results; The classification results are used to generate a data list according to the image ID of the display screen image.

[0018] The third aspect of the present application provides a device for detecting defects in a circuit area of ​​a micro display device, comprising: Processor, memory, input-output unit, and bus; The processor is connected to the memory, the input and output unit, and the bus; The memory stores a program, and the processor calls the program to execute the first aspect and any optional method of the first aspect.

[0019] A fourth aspect of the present application provides a computer-readable storage medium, on which a program is stored. When the program is executed on a computer, the program executes the first aspect and any optional method of the first aspect.

[0020] It can be seen from the above technical solutions that the embodiments of the present application have the following advantages: In the present application, the display screen to be tested is first photographed by a flying camera to collect the circuit area image of the display screen to be tested. The circuit area image is copied to generate a first circuit area image and a second circuit area image. The first circuit area image is subjected to grayscale expansion processing to generate a first template. The second circuit area image is subjected to grayscale corrosion processing to generate a second template. According to the preset circuit area limit sample diagram, the first template and the second template are respectively tested for the circuit defect area to generate a circuit dark defect area and a circuit bright defect area. Defect recognition detection is performed on the circuit dark defect area and the circuit bright defect area to generate circuit area defect data.

[0021] The circuit area defects are classified into bright defects and dark defects, and then hierarchical detection is performed. Specifically, the first template for dark defects and the second template for bright defects are generated by grayscale expansion and grayscale corrosion processing on the circuit area image. The pixels of the first template are analyzed one by one through the circuit area limit sample map to determine the dark defect area, and then the pixels of the first template are analyzed one by one through the circuit area limit sample map to generate the bright defect area. Finally, defect identification detection is performed on the circuit dark defect area and the circuit bright defect area to generate circuit area defect data. This method performs grayscale corrosion and grayscale expansion processing, and then performs regional analysis on the defect-free circuit area limit sample map to obtain the corresponding bright and dark defect areas. This method improves the screen defect detection accuracy of the display screen image containing the circuit area. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0023] Figure 1 A schematic diagram of an embodiment of a method for detecting defects in a circuit area of ​​a micro display device of the present application; Figure 2 A schematic diagram of an embodiment of a method for generating a bright defect area of ​​a circuit according to the present application; Figure 3 A schematic diagram of an embodiment of a method for obtaining dark defect compensation values ​​and bright defect compensation values ​​in the present application; Figure 4 A schematic diagram of an embodiment of the pre-processing method of the present application; Figure 5 A schematic diagram of an embodiment of a method for generating a circuit area limit sample diagram for the present application; Figure 6 A schematic diagram of an embodiment of a method for generating a circuit area limit sample diagram for the present application; Figure 7 A schematic diagram of an embodiment of a device for detecting defects in a circuit area of ​​a micro display device of the present application; Figure 8 A schematic diagram of another embodiment of the device for detecting defects in the circuit area of ​​a micro display device of the present application; Fig. 9 A schematic diagram of the display screen image of this application; Fig.10 A schematic diagram of the circuit area image of this application. DETAILED DESCRIPTION

[0024] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0025] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, wholes, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or combinations thereof.

[0026] It should also be understood that the term “and / or” used in the specification and appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0027] As used in the specification and appended claims of this application, the term "if" can be interpreted as "when" or "uponce" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "uponce it is determined" or "in response to determining" or "uponce [described condition or event] is detected" or "in response to detecting [described condition or event]", depending on the context.

[0028] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0029] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0030] In the prior art, as the application fields of display screens become more and more extensive and more and more functions are added, a sophisticated circuit structure is added inside or on the surface of the display screen. This type of structure will not have much impact on the detection of display defects, because the display screen layer is usually located on the circuit structure. However, since screen defects do not require screen display, and the circuit structure is usually a very thin circuit board, due to the complex internal structure of the circuit structure, it mainly presents blocks with different levels, and the overall area is large, concentrated distribution, and arranged inside the display screen. This type of display screen containing a circuit structure is prone to false detection and missed detection of screen defects in the corresponding circuit structure area, which reduces the accuracy of screen defect detection in the circuit area.

[0031] Based on this, the present application discloses a method, device and storage medium for detecting defects in the circuit area of ​​a micro display device, which are used to improve the screen defect detection accuracy of a display screen image containing a circuit area.

[0032] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0033] The method of the present application can be applied to a server, a device, a terminal or other devices with logic processing capabilities, and the present application does not limit this. For the convenience of description, the following description is made by taking the execution subject as an example of a terminal.

[0034] See also Figure 1 The present application provides an embodiment of a method for detecting defects in a circuit area of ​​a micro display device, comprising: 101. Use a flying camera to photograph the display screen to be tested, and collect an image of the circuit area of ​​the display screen to be tested; In this embodiment, the display screen to be tested is first fixed, the light source is turned on, and the display screen to be tested is photographed by an industrial line scan camera to generate a display screen image. The display screen to be tested contains a circuit structure. In this embodiment, the circuit structure is block-shaped as a whole, and there are irregular circuit modules.

[0035] The terminal first divides the display screen image into regional texture structures to generate a circuit area image, the purpose of which is to detect the circuit area image separately. In this embodiment, it can be determined by artificial demarcation or computer detection.

[0036] The textures of the image display area (corresponding to the display area appearance image), circuit area (corresponding to the circuit area appearance image), and boundary area (corresponding to the boundary area appearance image) are very different. Please refer to Fig. 9 , Fig. 9 is a display screen image. Please refer to Fig.10 , Fig.10 This is an image of the circuit area.

[0037] The circuit structure is located in the trapezoidal area at the lower side of the figure. It can be seen that this part has many shapes, including sawtooth circuit structure, strip circuit structure and other shapes. The area formed by these structures is the appearance image of the circuit area.

[0038] 102. Copy the circuit area image to generate a first circuit area image and a second circuit area image; The terminal copies the circuit area image to generate two circuit area images, which are defined as a first circuit area image and a second circuit area image.

[0039] 103. Perform grayscale expansion processing on the first circuit area image to generate a first template; 104. Perform grayscale corrosion processing on the second circuit area image to generate a second template; In this embodiment, the terminal generates a structural element according to the screen detection defect corresponding to the circuit area, and is specifically designed according to the size of the defect area of ​​the screen detection defect and the defect type.

[0040] The traditional defect convolution kernel mainly uses the size of the defect area to design the convolution kernel. This method is suitable for defects in the display area of ​​the display, but the effect will be much worse for defects in the circuit area.

[0041] In this embodiment, the types of circuit area defects are divided into circuit area bright defects and circuit area dark defects. In the design process, it is necessary to first determine the grayscale range of each defect based on the circuit area bright defects and circuit area dark defects. For example: obtain images of different circuit area defects, perform strict segmentation, and only leave the corresponding circuit defect area, perform grayscale mean detection on different circuit area defects, and classify them according to the grayscale mean of a certain circuit area defect into circuit area bright defects and circuit area dark defects. Determine the grayscale range of bright defects based on the grayscale mean of circuit area bright defects, and determine the grayscale range of dark defects in the same way. Then, determine the size range of each circuit defect in the circuit area bright defect, and generate structural elements exclusive to circuit area bright defects and circuit area dark defects in a specific size range and grayscale range.

[0042] Next, in this embodiment, the terminal performs grayscale expansion processing on the first circuit area image through the structural element of the dark defect in the circuit area to generate a first template.

[0043] In this embodiment, the terminal performs grayscale corrosion processing on the second circuit area image through the structural elements of the bright defects in the circuit area to generate a second template.

[0044] For the first template (grayscale image) I and the structural element B, the grayscale morphological dilation can be expressed as:

[0045] Where (x, y) represents the pixel position in the first template I, and (s, t) represents a position in the structure element B (here, the structure element B is the convolution kernel corresponding to the dark defect). This formula shows that for each pixel position, the maximum value of the sum of the pixel value within the coverage of the structure element and the structure element value is calculated, and the maximum value is used as the pixel value after the dilation operation.

[0046] Similarly, for the second template I and the structural element B, the grayscale morphological corrosion can be expressed as:

[0047] Among them, (x, y) represents a pixel position in the second template I, and (s, t) represents a position in the structural element B (here, the structural element B is the convolution kernel corresponding to the bright defect). This formula shows that for each pixel position, the minimum difference between the pixel value within the coverage of the structural element and the structural element value is calculated, and the minimum value is used as the pixel value after the corrosion operation.

[0048] 105. Detect circuit defect areas of the first template and the second template respectively according to a preset circuit area limit sample diagram to generate circuit dark defect areas and circuit bright defect areas; In this embodiment, the terminal obtains a standard sample screen, which is a defect-free display screen, and generates a sample screen shot image by shooting the standard sample screen under a suitable light source environment. The sample screen shot image is processed by the same partitioning method (a method of determining the circuit area by the display screen image) to generate a corresponding circuit area sample map. That is, before performing the circuit area appearance inspection, the terminal selects a standard sample screen of the same type as the display screen to be tested. A standard sample screen can be selected from all products, or one can be prepared in advance. The standard sample screen can be defined as a high-quality product, and the standard sample screen is required to be free of defects such as broken edges and corners. The standard sample screen is photographed and the circuit area is observed.

[0049] Next, the terminal uses the circuit area limit sample image and the pixel points on the first template for comparative analysis to detect areas that meet the circuit dark defects. At the same time, the terminal uses the circuit area limit sample image and the pixel points on the second template for comparative analysis to detect areas that meet the circuit bright defects.

[0050] 106. Perform defect identification detection on the dark defect area and the bright defect area of ​​the circuit to generate circuit area defect data.

[0051] The terminal performs defect recognition detection on the dark defect area and the bright defect area of ​​the circuit to generate circuit area defect data. In this embodiment, after the terminal compares the circuit defect area of ​​the first template and the second template, it can perform defect recognition detection on the dark defect area and the bright defect area of ​​the circuit. Specifically, artificial intelligence recognition can be used. Traditional artificial intelligence recognition of an entire display screen image will have a poorer detection effect, because there are fewer training samples for existing circuit area defects, which makes the simple artificial intelligence model less effective in detecting display screen images of larger areas. However, in this embodiment, the circuit area image is subjected to grayscale expansion processing and grayscale corrosion respectively, and then the defect area is screened out through the circuit area limited sample map, thereby reducing the detection amount of the artificial intelligence model. At the same time, this method can provide a large number of training samples, because different defect areas can be determined and identified, and finally the circuit area defect data is generated through the artificial intelligence model.

[0052] In this embodiment, the display screen to be tested is first photographed by a flying camera to collect the circuit area image of the display screen to be tested. The circuit area image is copied to generate a first circuit area image and a second circuit area image. The first circuit area image is subjected to grayscale expansion processing to generate a first template. The second circuit area image is subjected to grayscale corrosion processing to generate a second template. According to the preset circuit area limit sample diagram, the first template and the second template are respectively tested for circuit defect areas to generate circuit dark defect areas and circuit bright defect areas. Defect recognition detection is performed on the circuit dark defect area and the circuit bright defect area to generate circuit area defect data.

[0053] The circuit area defects are classified into bright defects and dark defects, and then hierarchical detection is performed. Specifically, the first template for dark defects and the second template for bright defects are generated by grayscale expansion and grayscale corrosion processing on the circuit area image. The pixels of the first template are analyzed one by one through the circuit area limit sample map to determine the dark defect area, and then the pixels of the first template are analyzed one by one through the circuit area limit sample map to generate the bright defect area. Finally, defect identification detection is performed on the circuit dark defect area and the circuit bright defect area to generate circuit area defect data. This method performs grayscale corrosion and grayscale expansion processing, and then performs regional analysis on the defect-free circuit area limit sample map to obtain the corresponding bright and dark defect areas. This method improves the screen defect detection accuracy of the display screen image containing the circuit area.

[0054] See also Figure 2 The present application provides an embodiment of a method for generating a bright defect area of ​​a circuit, comprising: 201. Obtain a dark defect compensation value and a bright defect compensation value; In this embodiment, the terminal first obtains the dark defect compensation value Diff-offset-1 and the bright defect compensation value Diff-offset-2. The dark defect compensation value is calculated based on the circuit limit pattern and the grayscale of the first template, and the bright defect compensation value is calculated based on the circuit limit pattern and the grayscale of the second template.

[0055] Because the circuit limit sample is actually collected in a standard environment scene, and the display screen image collected in real time may not reach the standard environment scene, there may be certain differences in the lighting environment at this time, especially in the flying camera system, the corresponding specific light source is turned on, but the actual light source may be different from the standard environment scene. At this time, it is necessary to calculate the compensation value of the first template and the second template according to the lighting difference.

[0056] 202. Perform pixel-by-pixel segmentation according to a preset dark defect threshold lower limit, a dark defect threshold upper limit, a circuit area limit sample map, a first template, and a dark defect compensation value to generate a circuit dark defect area; Next, the terminal obtains the lower limit of the dark defect threshold Diff-dark-lower and the upper limit of the dark defect threshold Diff-dark-upper, and calculates the dark defect parameter of each pixel according to the pixel Mn of the circuit area limit sample, the pixel CBn on the first template and the dark defect compensation value Diff-offset-1, and then compares it with the lower limit of the dark defect threshold Diff-dark-lower and the upper limit of the dark defect threshold Diff-dark-upper. The comparison mode of the dark defect parameter with the lower limit of the dark defect threshold Diff-dark-lower and the upper limit of the dark defect threshold Diff-dark-upper is as follows: CBn-Mn+Diff-offset-1>Diff-dark-lower CBn-Mn+Diff-offset-1<=Diff-dark-upper When the dark defect parameter is greater than the dark defect threshold lower limit Diff-dark-lower and the dark defect parameter is less than Diff-dark-upper, it means that the current pixel is a dark defect pixel. The dark defect parameter is calculated for each pixel according to this method to determine the circuit dark defect area composed of dark defect pixels.

[0057] 203. Perform pixel-by-pixel segmentation according to a preset bright defect threshold lower limit, a bright defect threshold upper limit, a circuit area limit sample map, a second template and a bright defect compensation value to generate a circuit bright defect area.

[0058] Next, the terminal obtains the lower limit of the bright defect threshold Diff-light-lower and the upper limit of the bright defect threshold Diff-light-upper. The terminal calculates the bright defect parameter of each pixel according to the pixel Mn of the circuit area limit sample, the pixel CSn on the second template and the bright defect compensation value Diff-offset-2, and then compares it with the lower limit of the bright defect threshold Diff-light-lower and the upper limit of the bright defect threshold Diff-light-upper. The comparison mode of the bright defect parameter with the lower limit of the bright defect threshold Diff-light-lower and the upper limit of the bright defect threshold Diff-light-upper is as follows: CSn-Mn+Diff-offset-2>Diff-light-lower CSn-Mn+Diff-offset-2<=Diff-light-upper When the bright defect parameter is greater than the bright defect threshold lower limit Diff-light-lower, or the bright defect parameter is less than Diff-light-upper, it means that the current pixel is a bright defect pixel. The bright defect parameter of each pixel is calculated according to this method to determine the circuit bright defect area composed of bright defect pixels.

[0059] This method can effectively distinguish between bright defect areas and dark defect areas on the display screen image. It not only subdivides the defects in the circuit area, but also identifies the subdivided defects by area through a unique defect detection method, thereby improving the accuracy of subsequent identification.

[0060] See also Figure 3 The present application provides an embodiment of a method for obtaining a dark defect compensation value and a bright defect compensation value, comprising: 301. Copy the preset circuit area limit sample diagram, and perform grayscale expansion processing and grayscale corrosion processing respectively to generate a third template and a fourth template; In this embodiment, the terminal first copies the circuit area limit sample image, performs grayscale expansion processing and grayscale corrosion processing using the structural elements of bright defects and dark defects respectively, and generates a third template and a fourth template. This step is to make the standard image undergo the same preprocessing.

[0061] 302. Obtain grayscale means of the first template, the second template, the third template, and the fourth template to generate a first grayscale mean, a second grayscale mean, a third grayscale mean, and a fourth grayscale mean; The terminal obtains the grayscale means of the first template, the second template, the third template and the fourth template, which are respectively calculated as the first grayscale mean u1, the second grayscale mean u2, the third grayscale mean u3 and the fourth grayscale mean u4.

[0062] 303. Obtaining a dark defect grayscale parameter and a bright defect grayscale parameter, wherein the dark defect grayscale parameter refers to the pixel grayscale data of each dark defect after grayscale expansion processing, and the bright defect grayscale parameter refers to the pixel grayscale data of each bright defect after grayscale corrosion processing; The terminal obtains the grayscale parameters of dark defects and bright defects. The grayscale parameters of dark defects refer to the grayscale data of the pixels of each dark defect after grayscale expansion processing. The grayscale parameters of bright defects refer to the grayscale data of the pixels of each bright defect after grayscale corrosion processing. For example, the grayscale value range of the sample image of each dark defect after grayscale expansion processing.

[0063] 304. Generate a dark defect compensation value by using the first grayscale mean, the third grayscale mean, and the dark defect grayscale parameter; The terminal generates a dark defect compensation value through the first grayscale mean, the third grayscale mean and the dark defect grayscale parameter. For example: first, the grayscale value range of the dark defect in each circuit area is centered and averaged to generate the grayscale median of the dark defect in each circuit area, and then the grayscale medians of all dark defects are averaged to generate the dark defect coefficient T1. The dark defect compensation value Diff-offset-1 is calculated through the dark defect coefficient T1, the first grayscale mean u1 and the third grayscale mean u3: Diff-offset-1=(u3-u1)[(T1+d) / (T1-d)] Wherein, d is the supplementary coefficient, which is usually an integer less than 5 and greater than -5. d depends on the size of T1 and u1. When T1 is greater than u1, d is 1 to 5 to increase the compensation value. When T1 is less than u1, d is -1 to -5 to reduce the compensation value.

[0064] 305. Generate a bright defect compensation value by using the second grayscale mean, the fourth grayscale mean, and the bright defect grayscale parameter.

[0065] The terminal generates a bright defect compensation value by using the second grayscale mean, the fourth grayscale mean and the bright defect grayscale parameter.

[0066] For example: First, the grayscale value range of each circuit area bright defect is averaged to generate the grayscale median of each circuit area bright defect, and then the grayscale medians of all bright defects are averaged to generate the bright defect coefficient T2. The bright defect compensation value Diff-offset-2 is calculated by the dark defect coefficient T2, the second grayscale mean u2 and the fourth grayscale mean u4: Diff-offset-2=(u4-u2)[(T2+d) / (T2-d))] Wherein, d is the supplementary coefficient, which is usually an integer less than 5 and greater than -5. d depends on the size of T2 and u2. When T2 is greater than u2, d is 1 to 5 to increase the compensation value. When T2 is less than u2, d is -1 to -5 to reduce the compensation value.

[0067] See also Figure 4 , the present application provides an embodiment of a preprocessing method, comprising: 401. Perform mean filter noise reduction processing or Gaussian filter noise reduction processing on the circuit area image.

[0068] In this embodiment, because the flying image is collected by the flying system, there will be a lot of flying noise, and the collected image needs to be pre-processed to reduce noise. First, the aperture focal length of the lens is fixed under the condition of meeting the working mode of the high-speed flying system, the position relationship between the platform and the flying camera is adjusted, the point light source is fixed on one side of the flying camera lens, and the camera parameters are saved. In addition, the images collected by the flying camera will have various noises. In order to ensure the image quality, the following noise reduction processing must be performed first: 1. Mean filtering: The processing method is: use a 3×3 mean filtering window to filter the image Iori to obtain the image Is.

[0069] 2. Gaussian filtering: The processing method is: use the Gaussian function as a filter to perform weighted averaging on the signal to smooth the signal and reduce noise, filter the image Iori, and obtain the image Ig.

[0070] While preprocessing the image, the template information is loaded. The template information is the standard image collected before the inspection, and the characteristic information of the wafer is extracted from the image and transmitted to the subsequent inspection module.

[0071] See also Figure 5 The present application provides an embodiment of a method for generating a circuit area limit sample diagram, comprising: 501. Capture images of the standard sample limit screen to generate a standard image of the product; In this embodiment, when creating a circuit area limit sample diagram, first, a standard image of a standard limit sample screen is collected.

[0072] 502. Generate an initial position of a circuit area and a buffer area on a standard image; The terminal generates an initial position of the circuit area and a buffer area on the standard image, and the buffer area is a screening range for all edge candidate points.

[0073] 503. Perform edge detection on the edges of the initial position of the circuit area from the outside to the inside, and select all candidate edge points according to a preset edge point parameter threshold; After the terminal presets the initial position and threshold of the possible circuit area, edge detection can be performed. Specifically, the edge of the initial position of the circuit area is detected from the outside to the inside, and all edge candidate points are screened out according to the preset edge point parameter threshold.

[0074] 504. Fit all candidate edge points and determine the coordinates of the angle points; The terminal then fits all the edge candidate points to determine the coordinates of the angle points. Specifically, the terminal fits each edge, and after fitting multiple straight lines, the coordinates of the intersection of two adjacent fitted straight lines can be determined.

[0075] 505. Generate a circuit area frame according to the coordinates at the angle point; The terminal generates a connection line according to the coordinates at the angle point, and generates a circuit area frame according to the coordinates at the angle point.

[0076] 506. Crop the standard image according to the circuit area frame to generate a circuit area limit sample image.

[0077] The terminal cuts the standard image according to the circuit area frame and finally generates a circuit area limit sample image. This method can also be used on the display screen image.

[0078] After extracting the complete circuit area image (circuit area limited sample image), record the circuit area image information (width, height, etc.).

[0079] The above method can divide the entire circuit area well and reduce the amount of calculation.

[0080] See also Figure 6 The present application provides an embodiment of a method for generating a circuit area limit sample diagram, comprising: 601. Cut the dark defect area of ​​the circuit of the first template and the bright defect area of ​​the circuit of the second template to generate a dark defect sub-area and a bright defect sub-area; 602. Send the cut dark defect sub-region and the bright defect sub-region to a classification network for classification to generate a classification result; 603. Generate a data list based on the classification result according to the image ID of the display screen image.

[0081] In this embodiment, the terminal needs to integrate all bright and dark defects in the circuit area, crop the bright and dark defect areas, use the ResNet classification network to accurately classify, refine each defect type, and save the output for customer display. The specific operation steps are as follows: 1. Obtain all bright and dark defect areas and cut them out; 2. Send the cut defective area to the classification network for classification; 3. Get all classification results; 4. Generate a data list (including all feature parameters) based on the image ID; 5. Replace the classification results into the data list; 6. Output data list data.

[0082] This method can accurately identify defective areas, reducing the amount of calculation. It can also generate a large number of training samples to improve the accuracy of the artificial intelligence model.

[0083] See also Figure 7 The present application provides an embodiment of a device for detecting defects in a circuit area of ​​a micro display device, comprising: The sixth generating unit 701 is used to collect images of the standard sample limit screen to generate a standard image of the product; The seventh generating unit 702 is used to generate the initial position of the circuit area and the buffer area on the standard image; The screening unit 703 is used to perform edge detection on the edge of the initial position of the circuit area from the outside to the inside, and screen out all the candidate edge points according to a preset edge point parameter threshold; A determination unit 704 is used to fit all edge candidate points and determine the coordinates of the angle points; An eighth generating unit 705, configured to generate a circuit area frame according to the coordinates at the angle point; A ninth generating unit 706, configured to crop the standard image according to the circuit area frame to generate a circuit area limit sample image; The acquisition unit 707 is used to take a picture of the display screen to be tested by using a flying camera to acquire a circuit area image of the display screen to be tested; The filtering unit 708 is used to perform mean filtering or Gaussian filtering noise reduction processing on the circuit area image.

[0084] A first generating unit 709, configured to copy the circuit area image to generate a first circuit area image and a second circuit area image; The second generating unit 710 is used to perform grayscale expansion processing on the first circuit area image to generate a first template; The third generating unit 711 is used to perform grayscale corrosion processing on the second circuit area image to generate a second template; The fourth generating unit 712 is used to detect the circuit defect area of ​​the first template and the second template respectively according to the preset circuit area limit sample diagram, and generate a circuit dark defect area and a circuit bright defect area; Optionally, the fourth generating unit 712 includes: An acquisition module 7121 is used to acquire a dark defect compensation value and a bright defect compensation value; Optionally, the acquisition module 7121 includes: The preset circuit area limit sample diagram is copied, and grayscale expansion processing and grayscale corrosion processing are performed respectively to generate a third template and a fourth template; Obtaining grayscale means of the first template, the second template, the third template, and the fourth template to generate a first grayscale mean, a second grayscale mean, a third grayscale mean, and a fourth grayscale mean; Obtaining dark defect grayscale parameters and bright defect grayscale parameters, wherein the dark defect grayscale parameters refer to the pixel grayscale data of each dark defect after grayscale expansion processing, and the bright defect grayscale parameters refer to the pixel grayscale data of each bright defect after grayscale corrosion processing; Generate a dark defect compensation value by using the first grayscale mean, the third grayscale mean and the dark defect grayscale parameter; A bright defect compensation value is generated by the second grayscale mean, the fourth grayscale mean, and the bright defect grayscale parameter.

[0085] The first generating module 7122 is used to perform pixel-by-pixel segmentation according to a preset dark defect threshold lower limit, dark defect threshold upper limit, circuit area limit sample map, first template and dark defect compensation value to generate a circuit dark defect area; The second generation module 7123 is used to perform pixel-by-pixel segmentation according to the preset bright defect threshold lower limit, bright defect threshold upper limit, circuit area limit sample map, second template and bright defect compensation value to generate a circuit bright defect area.

[0086] The fifth generating unit 713 is used to perform defect recognition detection on the circuit dark defect area and the circuit bright defect area to generate circuit area defect data.

[0087] Optionally, the fifth generating unit 713 includes: Cutting the dark defect area of ​​the circuit of the first template and the bright defect area of ​​the circuit of the second template to generate a dark defect sub-area and a bright defect sub-area; The cut dark defect sub-region and the bright defect sub-region are sent to the classification network for classification to generate classification results; The classification results are used to generate a data list according to the image ID of the display screen image.

[0088] See also Figure 8 The present application provides a device for detecting defects in a circuit area of ​​a micro display device, comprising: Processor 801 , memory 802 , input-output unit 803 , and bus 804 .

[0089] The processor 801 is connected to the memory 802 , the input and output unit 803 , and the bus 804 .

[0090] The memory 802 stores a program, and the processor 801 calls the program to execute the following steps: Figure 1 , Figure 2 and Figure 3 , Figure 4 , Figure 5 and Figure 6 The method in .

[0091] The present application provides a computer-readable storage medium, on which a program is stored, and when the program is executed on a computer, the program performs the following steps: Figure 1 , Figure 2 and Figure 3 , Figure 4 , Figure 5 and Figure 6 The method in .

[0092] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0093] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0094] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0095] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0096] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, read-only memory), random access memory (RAM, random access memory), disk or optical disk and other media that can store program code.

Claims

1. A method for detecting defects in a circuit area of ​​a micro display device, characterized in that: include: The display screen to be tested is photographed by a flying camera to collect a circuit area image of the display screen to be tested; Copying the circuit area image to generate a first circuit area image and a second circuit area image; Performing grayscale expansion processing on the first circuit area image to generate a first template; Performing grayscale corrosion processing on the second circuit area image to generate a second template; According to a preset circuit area limit sample diagram, the first template and the second template are respectively tested for circuit defect areas to generate circuit dark defect areas and circuit bright defect areas; Defect recognition detection is performed on the dark defect area of ​​the circuit and the bright defect area of ​​the circuit to generate circuit area defect data.

2. The method according to claim 1, characterized in that According to a preset circuit area limit sample diagram, the first template and the second template are respectively tested for circuit defect areas to generate circuit dark defect areas and circuit bright defect areas, including: Obtaining dark defect compensation values ​​and bright defect compensation values; Perform pixel-by-pixel segmentation according to a preset dark defect threshold lower limit, a dark defect threshold upper limit, a circuit area limit sample diagram, the first template, and the dark defect compensation value to generate a circuit dark defect area; A circuit bright defect area is generated by performing pixel-by-pixel segmentation according to a preset bright defect threshold lower limit, a bright defect threshold upper limit, a circuit area limit sample diagram, the second template and the bright defect compensation value.

3. The method according to claim 2, characterized in that Obtain dark defect compensation values ​​and bright defect compensation values, including: The preset circuit area limit sample diagram is copied, and grayscale expansion processing and grayscale corrosion processing are performed respectively to generate a third template and a fourth template; Obtaining grayscale means of the first template, the second template, the third template, and the fourth template to generate a first grayscale mean, a second grayscale mean, a third grayscale mean, and a fourth grayscale mean; Obtaining a dark defect grayscale parameter and a bright defect grayscale parameter, wherein the dark defect grayscale parameter refers to the pixel grayscale data of each dark defect after grayscale expansion processing, and the bright defect grayscale parameter refers to the pixel grayscale data of each bright defect after grayscale corrosion processing; Generate a dark defect compensation value by using the first grayscale mean, the third grayscale mean and the dark defect grayscale parameter; A bright defect compensation value is generated by using the second grayscale mean, the fourth grayscale mean, and the bright defect grayscale parameter.

4. The method according to any one of claims 1 to 3, characterized in that After capturing the circuit area image of the display screen to be tested by a flying camera, and before copying the circuit area image to generate the first circuit area image and the second circuit area image, the method further includes: The circuit area image is subjected to mean filter noise reduction processing or Gaussian filter noise reduction processing.

5. The method according to any one of claims 1 to 3, characterized in that Before photographing the display screen to be tested by using a flying camera to collect the circuit area image of the display screen to be tested, the method further includes: Capture images of the standard sample limit screen to generate standard images of the product; Generating a circuit area initial position and a buffer area on the standard image; Perform edge detection on the edge of the initial position of the circuit area from the outside to the inside, and screen out all candidate edge points according to a preset edge point parameter threshold; Fit all edge candidate points and determine the coordinates of the angle points; Generate a circuit area frame according to the coordinates at the angle point; The standard image is cropped according to the circuit area frame to generate a circuit area limit sample image.

6. The method according to any one of claims 1 to 3, characterized in that Performing defect recognition detection on the dark defect area and the bright defect area of ​​the circuit to generate circuit area defect data includes: Cutting the circuit dark defect area of ​​the first template and the circuit bright defect area of ​​the second template to generate a dark defect sub-area and a bright defect sub-area; The cut dark defect sub-region and the bright defect sub-region are sent to the classification network for classification to generate classification results; The classification result is used to generate a data list according to the image ID of the display screen image.

7. A device for detecting defects in a circuit area of ​​a micro display device, characterized in that: include: A collection unit, used to take a picture of the display screen to be tested by using a flying camera, and collect a circuit area image of the display screen to be tested; A first generating unit, configured to copy the circuit area image to generate a first circuit area image and a second circuit area image; A second generating unit, configured to perform grayscale expansion processing on the first circuit area image to generate a first template; A third generating unit, configured to perform grayscale corrosion processing on the second circuit area image to generate a second template; A fourth generating unit, configured to detect circuit defect areas of the first template and the second template respectively according to a preset circuit area limit sample diagram, and generate circuit dark defect areas and circuit bright defect areas; The fifth generating unit is used to perform defect identification detection on the dark defect area of ​​the circuit and the bright defect area of ​​the circuit to generate circuit area defect data.

8. The device according to claim 7, characterized in that The fourth generation unit comprises: An acquisition module, used for acquiring a dark defect compensation value and a bright defect compensation value; A first generating module, configured to perform pixel-by-pixel segmentation according to a preset dark defect threshold lower limit, a dark defect threshold upper limit, a circuit area limit sample diagram, the first template and the dark defect compensation value to generate a circuit dark defect area; The second generation module is used to perform pixel-by-pixel segmentation according to a preset bright defect threshold lower limit, a bright defect threshold upper limit, a circuit area limit sample map, the second template and the bright defect compensation value to generate a circuit bright defect area.

9. A device for detecting defects in a circuit area of ​​a micro display device, characterized in that: include: Processor, memory, input-output unit, and bus; The processor is connected to the memory, the input and output unit, and the bus; The memory stores a program, and the processor calls the program to execute the method according to any one of claims 1 to 6.

10. A computer-readable storage medium having a program stored thereon, wherein the program, when executed on a computer, performs the method according to any one of claims 1 to 6.

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