Gluing detection method and device and computer equipment

Abstract

The embodiment of the application provides a gluing detection method and device and computer equipment, and relates to the technical field of display. First, a first image of a glass substrate coated with a glue layer is acquired; then, a first edge of the glass substrate in the first image and a second edge of the glue layer in the first image are identified; then, whether residual glue exists in a target region between the edge of the glass substrate and the edge of the glue layer is detected, and if residual glue exists in the target region, the residual glue is marked in the target region. Through the above scheme, whether residual glue exists in the non-gluing region between the edge of the glass substrate and the edge of the glue layer can be detected, the glass substrate with residual glue is identified in time and corresponding processing is performed, process defects caused by residual glue when the part of the glass substrate directly undergoes subsequent process procedures are avoided, and the process yield of the display panel is improved.

Description

Technical Field

[0001] This application relates to the field of display technology, and more specifically, to a method, apparatus, and computer equipment for detecting adhesive coating. Background Technology

[0002] A display panel is a precision device composed of multiple film layers. During its manufacturing, adhesives are often applied to form some of these layers. However, due to the significant decline in the scraping performance of the squeegee towards the end of its lifespan, a small amount of adhesive (such as PI adhesive) remains in the nozzle. This residue forms in non-coated areas during the coating process, causing uneven mask placement and affecting the vapor deposition effect in subsequent processes. Improving the detection efficiency and identification accuracy of residual adhesive is a pressing technical problem that needs to be solved by those skilled in the art. Summary of the Invention

[0003] In order to overcome the technical problems mentioned in the above technical background, this application provides a method, apparatus and computer equipment for detecting adhesive coating.

[0004] A first aspect of this application provides a method for detecting adhesive coating, the method comprising:

[0005] A first image of a glass substrate coated with an adhesive layer is obtained, wherein the edges of the glass substrate are all located within the first image;

[0006] Edge recognition is performed on the first image to identify the first edge of the glass substrate and the second edge of the adhesive layer in the first image;

[0007] Detect whether there is residual adhesive in the target area between the edge of the glass substrate and the edge of the adhesive layer. If there is residual adhesive in the target area, mark the residual adhesive in the target area.

[0008] In one possible implementation of this application, the method further includes:

[0009] Calculate the distance between the corresponding first edge and the second edge;

[0010] The distance is compared with a preset distance threshold. If the distance is greater than or equal to the preset distance threshold, it is determined that the distance between the second edge of the adhesive layer and the first edge of the glass substrate is within the preset control specification. If the distance is less than the preset distance threshold, it is determined that the distance between the second edge of the adhesive layer and the first edge of the glass substrate is outside the preset control specification.

[0011] In one possible implementation of this application, the step of acquiring a first image of a glass substrate coated with an adhesive layer includes:

[0012] Acquire images of glass substrates coated with adhesive layers captured by an image acquisition device;

[0013] The glass substrate image is processed to obtain the first image, wherein the image processing includes noise reduction and grayscale conversion.

[0014] In one possible implementation of this application, the step of performing edge recognition on the first image to identify the first edge of the glass substrate and the second edge of the adhesive layer in the first image includes:

[0015] An edge detection operator is used to calculate the gradient magnitude and gradient direction of pixels in the first image, and a non-maximum suppression method is applied to determine the first edge to be determined of the glass substrate in the first image and the second edge to be determined of the adhesive layer in the first image.

[0016] The gradient magnitude of each pixel in the first and second edges to be determined is compared with a first gradient magnitude threshold and a second gradient magnitude threshold, respectively, wherein the first gradient magnitude threshold is greater than the second gradient magnitude threshold. When the gradient magnitude of a pixel is greater than or equal to the first gradient magnitude threshold, the pixel is determined to be an edge pixel. When the gradient magnitude of a pixel is less than the first gradient magnitude threshold but greater than or equal to the second gradient magnitude threshold, it is detected whether the pixel is connected to a determined edge pixel. If connected, the pixel is determined to be an edge pixel; otherwise, the pixel is determined to be a non-edge pixel. When the gradient magnitude of a pixel is less than the first gradient magnitude threshold and less than the second gradient magnitude threshold, the pixel is determined to be a non-edge pixel. The first edge is formed by the determined edge pixels in the first edge to be determined, and the second edge is formed by the determined edge pixels in the second edge to be determined.

[0017] In one possible implementation of this application, after the step of performing edge recognition on the first image to identify the first edge of the glass substrate and the second edge of the adhesive layer in the first image, the method further includes:

[0018] The first image after edge recognition is segmented to obtain multiple sub-images;

[0019] Preferably, the adhesive layer comprises a first adhesive layer and a second adhesive layer stacked on top of each other, and the second edge comprises the edge of the first adhesive layer in the first image and the edge of the second adhesive layer in the first image.

[0020] In one possible embodiment of this application, the step of detecting whether there is residual adhesive in a target area between the edge of the glass substrate and the edge of the adhesive layer, and marking the residual adhesive in the target area if there is residual adhesive, includes:

[0021] The first edge of the glass substrate and the second edge of the adhesive layer are identified using a moving average method, forming a mask for identifying the target area between the first edge of the glass substrate and the second edge of the adhesive layer;

[0022] The mask is used to retain only the image information of the target region in the first image;

[0023] Detect whether there are pixels in the target area with a gray level value greater than a preset gray level threshold. When there are pixels with a gray level value greater than the preset gray level threshold, determine that there is residual adhesive at the position corresponding to the pixel. The gray level value of the adhesive layer in the first image is greater than the preset gray level threshold.

[0024] Mark the residual adhesive in the target area;

[0025] Preferably, when the residual adhesive is present in the target area, the method further includes:

[0026] The output includes the image name of the sub-image of the residual adhesive and the coordinate position information of the residual adhesive in the corresponding sub-image.

[0027] In one possible implementation of this application, the step of calculating the distance between the first edge and the second edge includes:

[0028] Calculate the number of pixels located between the corresponding first edge and the second edge and arranged along a direction perpendicular to the extension of the first edge or the extension of the second edge, and use the number of pixels as the distance.

[0029] In one possible implementation of this application, when the distance between the second edge of the adhesive layer and the first edge of the glass substrate is within a preset control specification, the method further includes:

[0030] Output the identification information of the glass substrate, the position information of the first edge and the second edge, and the corresponding distance between the first edge and the second edge;

[0031] Preferably, when the distance between the second edge of the adhesive layer and the first edge of the glass substrate is outside the preset control specification, the method further includes:

[0032] The output includes the identification information of the glass substrate, the position information of the first edge and the second edge located outside the preset control specifications, and the distance between the first edge and the second edge located outside the preset control specifications.

[0033] A second aspect of this application also provides an adhesive coating detection device, the device comprising:

[0034] An acquisition module is used to acquire a first image of a glass substrate coated with an adhesive layer, wherein the edges of the glass substrate are all located within the first image;

[0035] The recognition module is used to perform edge recognition on the first image, and to identify the first edge of the glass substrate and the second edge of the adhesive layer in the first image;

[0036] The detection module is used to detect whether there is residual adhesive in the target area between the edge of the glass substrate and the edge of the adhesive layer. If there is residual adhesive in the target area, the residual adhesive is marked in the target area.

[0037] A third aspect of this application also provides a computer device, the computer device including a processor, a computer-readable storage medium and a communication interface, the computer-readable storage medium, the communication interface and the processor being connected via a bus system, the computer-readable storage medium being used to store programs, instructions or code, and the processor being used to execute the programs, instructions or code in the computer-readable storage medium to perform the adhesive coating detection method according to any one of the first aspects.

[0038] A fourth aspect of this application also provides a computer-readable storage medium storing instructions that, when executed, cause a computer device to perform the adhesive coating detection method described in any one of the first aspects.

[0039] The solution provided in this application firstly acquires a first image of a glass substrate coated with an adhesive layer; then, it identifies a first edge of the glass substrate and a second edge of the adhesive layer in the first image; next, it detects whether there is residual adhesive in a target area between the edge of the glass substrate and the edge of the adhesive layer. If residual adhesive is present in the target area, it marks the residual adhesive in the target area. This solution allows for the detection of residual adhesive in the non-adhesive-coated area between the edge of the glass substrate and the edge of the adhesive layer, enabling timely identification and appropriate processing of glass substrates with residual adhesive. This avoids process defects caused by residual adhesive when the glass substrate is directly subjected to subsequent processing steps, thereby improving the process yield of the display panel. Attached Figure Description

[0040] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0041] Figure 1 A flowchart illustrating the adhesive coating detection method provided in this embodiment is shown.

[0042] Figure 2 A schematic diagram illustrating the distribution of the glass substrate and adhesive layer in the first image is shown in this embodiment;

[0043] Figure 3 A partial flowchart of the adhesive coating detection method provided in this embodiment is illustrated.

[0044] Figure 4 An example of implementation is provided. Figure 1 A flowchart illustrating step S120;

[0045] Figure 5 An example of implementation is provided. Figure 1 A flowchart illustrating step S130;

[0046] Figure 6 A schematic diagram illustrating the functional modules of the adhesive coating detection device provided in this embodiment is shown.

[0047] Figure 7 A schematic diagram illustrating the structural framework of the computer device provided in this embodiment for implementing the above-described adhesive coating detection method is shown. Detailed Implementation

[0048] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0049] The present invention will now be described in detail with reference to the accompanying drawings. The specific operation methods in the method embodiments can also be applied to the device embodiments or system embodiments.

[0050] Please see Figure 1The adhesive coating detection method provided in this application embodiment can be executed by a computer device. In other embodiments, the order of some steps in the adhesive coating detection method of this application embodiment can be interchanged according to actual needs, or some steps can be omitted or deleted. The detailed steps of the adhesive coating detection method executed by the computer device are described below.

[0051] Step S110: Obtain a first image of the glass substrate coated with an adhesive layer.

[0052] In this embodiment, the first image can be a grayscale image, in which the edges of the glass substrate are all located within the first image. For example, please refer to... Figure 2 , Figure 2 The example illustrates the positional relationship between the glass substrate and the adhesive layer in the first image. The edges of the adhesive layer 20 are all located within the glass substrate 10, and the edges of the glass substrate 10 are all located within the first image. The shape of the adhesive layer 20 is the same as the shape of the glass substrate 10. For example, the shape of the glass substrate 10 is rectangular, and the shape of the adhesive layer 20 is also rectangular. The edges of the adhesive layer 20 can be parallel to the corresponding edges of the glass substrate 10.

[0053] Step S120: Edge recognition is performed on the first image to identify the first edge 121 of the glass substrate 10 in the first image and the second edge 201 of the adhesive layer 20 in the first image.

[0054] An edge recognition algorithm is used to perform edge recognition on the first image, and the first edge 121 of the glass substrate 10 and the second edge 201 of the adhesive layer 20 in the first image are identified.

[0055] Step S130: Detect whether there is residual adhesive in the target area 110 between the first edge 121 of the glass substrate and the second edge 201 of the adhesive layer. If there is residual adhesive in the target area 110, mark the residual adhesive in the target area 110.

[0056] In this embodiment, after determining the first edge 121 and the second edge 201, the non-adhesive area on the glass substrate 10 can be determined, that is, the target area 110 between the edge of the glass substrate 10 and the edge of the adhesive layer 20. The presence of residual adhesive in the target area 110 is detected. If residual adhesive is present, it is marked in the target area 110, which facilitates the treatment of residual adhesive in the target area 110.

[0057] The above-described solution provided in this embodiment can detect whether there is residual adhesive in the non-adhesive area between the edge of the glass substrate 10 and the edge of the adhesive layer 20, and promptly identify and process the glass substrate 10 with residual adhesive, thereby avoiding process defects caused by the presence of residual adhesive when the glass substrate 10 is directly processed in subsequent processes, and improving the process yield of the display panel.

[0058] Further, please refer to Figure 3 The adhesive coating detection method provided in this embodiment may further include the following steps.

[0059] Step S140: Calculate the distance between the corresponding first edge 121 and the second edge 201.

[0060] In the embodiment, the distance between the first edge 121 and the corresponding second edge 201 is calculated. For example, if the first edge 121 is the edge of a certain side (left side) of the glass substrate 10, then the second edge 201 is the edge corresponding to the first edge 121 on that side (left side), that is, the second edge 201 is the edge of the adhesive layer 20 on that side (left side).

[0061] In this embodiment, the distance between the first edge 121 and the second edge 201 can be obtained by: calculating the number of pixels located between the corresponding first edge 121 and the second edge 201 and arranged along the direction perpendicular to the extension of the first edge 121 or the extension of the second edge 201, and using the number of pixels as the distance.

[0062] Step S150: The distance is compared with a preset distance threshold. If the distance is greater than or equal to the preset distance threshold, it is determined that the distance between the second edge 201 of the adhesive layer 20 and the first edge 121 of the glass substrate 10 is within the preset control specification. If the distance is less than the preset distance threshold, it is determined that the distance between the second edge 201 of the adhesive layer 20 and the first edge 121 of the glass substrate 10 is outside the preset control specification.

[0063] By comparing the distance between the first edge 121 and the corresponding second edge 201 with a preset distance threshold, it is determined whether the distance between the two is within the preset control specifications. The inventors found that when the distance between the two is not within the preset control specifications, the probability of process defects increases. Therefore, in this embodiment, if it is determined that the distance between the two is not within the preset control specifications, the position area of ​​the adhesive layer 20 on the glass substrate 10 can be changed by adjusting the adhesive coating parameters so that the distance between the two is within the preset control specifications after adjustment.

[0064] Furthermore, in this embodiment, step S110 can be implemented in the following way.

[0065] First, an image of a glass substrate coated with an adhesive layer is acquired by an image acquisition device.

[0066] The image acquisition device can be a CCD camera, and the image on the glass substrate is a color image.

[0067] Next, image processing is performed on the glass substrate image to obtain the first image.

[0068] To improve the accuracy of subsequent edge recognition and reduce the amount of data processing, the glass substrate image can be denoised first, and then the denoised glass substrate image can be converted to grayscale to obtain the corresponding grayscale image, which is then used as the first image.

[0069] In this embodiment, please refer to Figure 4 Step S120 can be achieved through the following steps.

[0070] Step S1201: The gradient magnitude and gradient direction of the pixels in the first image are calculated using an edge detection operator, and the non-maximum suppression method is applied to determine the first edge to be determined of the glass substrate in the first image and the second edge to be determined of the adhesive layer in the first image.

[0071] For example, an edge detection operator (such as the Sobel operator) can be used to calculate the gradient magnitude and gradient direction of pixels in the first image. Specifically, a 3*3 convolution template can be applied to the first image from the pixel row and pixel column directions respectively to obtain the gradient magnitude and gradient direction of pixels in the first image. Non-edge pixels are filtered out using a non-maximum suppression method. Specifically, the grayscale values ​​of pixels with non-maximum gradient magnitudes in multiple consecutive pixels in the same gradient direction are set to zero (i.e., only the grayscale values ​​of pixels with maximum values ​​are retained). This can make the edges clearer, thus obtaining the first undetermined edge of the glass substrate in the first image and the second undetermined edge of the adhesive layer in the first image.

[0072] Step S1202: Compare the gradient magnitude of each pixel in the first and second edges to be determined with a first gradient magnitude threshold and a second gradient magnitude threshold, respectively, wherein the first gradient magnitude threshold is greater than the second gradient magnitude threshold; when the gradient magnitude of a pixel is greater than or equal to the first gradient magnitude threshold, the pixel is determined to be an edge pixel; when the gradient magnitude of a pixel is less than the first gradient magnitude threshold but greater than or equal to the second gradient magnitude threshold, detect whether the pixel is connected to a determined edge pixel; if connected, the pixel is determined to be an edge pixel; otherwise, the pixel is determined to be a non-edge pixel; when the gradient magnitude of a pixel is less than the first gradient magnitude threshold and less than the second gradient magnitude threshold, the pixel is determined to be a non-edge pixel; the determined edge pixels in the first edge to be determined form the first edge, and the determined edge pixels in the second edge to be determined form the second edge.

[0073] In the above steps, double-threshold processing is adopted to determine the final edges. Among them, if the gradient value of a pixel is greater than or equal to the upper bound of the threshold (the first gradient amplitude threshold), the pixel will be considered as an edge pixel (also known as a strong edge pixel) for sure; if the gradient value of the pixel is less than the upper bound of the threshold and greater than or equal to the lower bound of the threshold (the second gradient amplitude threshold), it is checked whether the pixel is connected to the confirmed edge pixels. If it is connected, the pixel is also regarded as an edge pixel, otherwise the pixel is regarded as a non-edge pixel; if the gradient value of the pixel is less than the lower bound of the threshold, the pixel is directly regarded as a non-edge pixel.

[0074] In a possible implementation manner of this embodiment, the size of the glass substrate may be relatively large, and the size of the obtained first image will also be large. For the convenience of subsequent image processing, after step S120, the first image can be segmented to obtain multiple sub-images.

[0075] Optionally, in a possible implementation manner of this embodiment, the adhesive layer 20 may be formed by laminating multiple adhesive layers. Exemplarily, the adhesive layer 20 may include a first adhesive layer and a second adhesive layer that are laminated with each other. The second edge 201 includes the edge of the first adhesive layer in the first image and the edge of the second adhesive layer in the first image.

[0076] Further, in this embodiment, please refer to Figure 5 , step S130 can be implemented through the following steps.

[0077] Step S1301, use the moving average method to identify the first edge 121 of the glass substrate 10 and the second edge 201 of the adhesive layer 20, and form a mask for identifying the target area 110 between the first edge 121 of the glass substrate 10 and the second edge 201 of the adhesive layer 20.

[0078] Among them, in the moving average method, let the observation sequence be y1,...,y , take the number of terms N for moving average, where N < T. The calculation formula for a simple moving average value at one time is: <00​​​​​​​​​​​​​​​​The first edge 121 of the glass substrate 10 and the second edge 201 of the adhesive layer 20 can be identified by a moving average method, and a mask is formed for identifying the target region 110 between the first edge 121 of the glass substrate 10 and the second edge 201 of the adhesive layer 20. For example, the mask has the same size and pixel arrangement as the first image, wherein the grayscale value of the region corresponding to the target region 110 in the mask is 1, and the grayscale value of other regions is 0.

[0085] Step S1302: Use a mask to retain only the image information of the target area in the first image.

[0086] By multiplying the first image and the mask, the target region 110 between the first edge 121 and the second edge 201 can be extracted separately.

[0087] Step S1303: Detect whether there are pixels in the target area 110 with grayscale values ​​greater than a preset grayscale threshold. If there are pixels with grayscale values ​​greater than the preset grayscale threshold, determine that there is residual adhesive at the corresponding position of the pixel.

[0088] In this embodiment, the grayscale value of the adhesive layer 20 in the first image is greater than a preset grayscale threshold. That is, in the first image, the adhesive layer 20 corresponds to a bright image. For example, in a binarized image, a pixel area with a grayscale value of 1 can be identified as residual adhesive; in a grayscale image, a region formed by pixels with a grayscale value greater than a preset grayscale threshold (such as grayscale value 220) can be identified as residual adhesive.

[0089] Step S1304: Mark the residual adhesive in the target area 110.

[0090] For example, residual adhesive can be marked in the target area 110 using a label box, so that operators can quickly locate the location of the residual adhesive and improve the efficiency of residual adhesive treatment.

[0091] To further improve the efficiency of residual adhesive removal, the adhesive detection method provided in this embodiment also includes outputting the image name of the sub-image containing the residual adhesive and the coordinate position information of the residual adhesive in the corresponding sub-image.

[0092] Furthermore, when the distance between the second edge 201 of the adhesive layer 20 and the first edge 121 of the glass substrate 10 is within a preset control specification, the adhesive coating detection method provided in this embodiment further includes:

[0093] The system outputs identification information of the glass substrate 10 (e.g., the ID of the glass substrate), position information of the first edge 121 and the second edge 201, and the distance between the corresponding first edge 121 and second edge 201. Operators or computer equipment can adjust the adhesive coating parameters in a timely manner based on the changing trend of the distance between the first edge 121 and the second edge 201, preventing the distance between the second edge 201 of the adhesive layer 20 and the first edge 121 of the glass substrate 10 from exceeding preset control specifications.

[0094] Furthermore, when the distance between the second edge 201 of the adhesive layer 20 and the first edge 121 of the glass substrate 10 is outside the preset control specification, the adhesive coating detection method provided in this embodiment further includes:

[0095] The system outputs identification information of the glass substrate 10 (e.g., the ID of the glass substrate), position information of the first edge 121 and the second edge 201 located outside the preset control specifications, and the distance between the first edge 121 and the second edge 201 located outside the preset control specifications. Operators or computer equipment can quickly locate abnormal glue application locations through the above output, improving the efficiency of handling glue application abnormalities.

[0096] Based on the same inventive concept, this embodiment also provides an adhesive coating detection device, please refer to... Figure 6 , Figure 6 This is a functional module diagram of the adhesive application detection device 100 provided in this embodiment. This embodiment divides the adhesive application detection device 100 into functional modules according to the above method embodiments. That is, the following functional modules corresponding to the adhesive application detection device 100 can be used to execute the above method embodiments. The adhesive application detection device 100 may include an acquisition module 110, an identification module 120, and a detection module 130. The functions of each functional module of the adhesive application detection device 100 will be described in detail below.

[0097] The acquisition module 110 is used to acquire a first image of a glass substrate coated with an adhesive layer.

[0098] In this embodiment, the first image can be a grayscale image, in which the edges of the glass substrate are all located within the first image. For example, please refer again... Figure 2 , Figure 2 The example illustrates the positional relationship between the glass substrate and the adhesive layer in the first image. The edges of the adhesive layer 20 are all located within the glass substrate 10, and the edges of the glass substrate 10 are all located within the first image. The shape of the adhesive layer 20 is the same as the shape of the glass substrate 10. For example, the shape of the glass substrate 10 is rectangular, and the shape of the adhesive layer 20 is also rectangular. The edges of the adhesive layer 20 can be parallel to the corresponding edges of the glass substrate 10.

[0099] The acquisition module 110 can be used to perform the above-mentioned step S110. For a detailed description of the implementation of the acquisition module 110, please refer to the above-mentioned detailed description of step S110.

[0100] The recognition module 120 is used to perform edge recognition on the first image and identify the first edge 121 of the glass substrate 10 in the first image and the second edge 201 of the adhesive layer 20 in the first image.

[0101] The recognition module 120 uses an edge recognition algorithm to perform edge recognition on the first image, and identifies the first edge 121 of the glass substrate 10 in the first image and the second edge 201 of the adhesive layer 20 in the first image.

[0102] The identification module 120 can be used to perform the above-described step S120. For a detailed description of the implementation of the identification module 120, please refer to the above-described detailed description of step S120.

[0103] The detection module 130 is used to detect whether there is residual adhesive in the target area 110 between the first edge 121 of the glass substrate and the second edge 201 of the adhesive layer. If there is residual adhesive in the target area 110, the residual adhesive is marked in the target area 110.

[0104] In this embodiment, after determining the first edge 121 and the second edge 201, the non-adhesive area on the glass substrate 10 can be determined, that is, the target area 110 between the edge of the glass substrate 10 and the edge of the adhesive layer 20. The presence of residual adhesive in the target area 110 is detected. If residual adhesive is present, it is marked in the target area 110, which facilitates the treatment of residual adhesive in the target area 110.

[0105] The detection module 130 can be used to perform the above-described step S130. For a detailed description of the implementation of the detection module 130, please refer to the above-described detailed description of step S130.

[0106] Furthermore, please refer to again Figure 6 The adhesive coating detection device 100 provided in this embodiment also includes a calculation module 140 and a judgment module 150.

[0107] The calculation module 140 is used to calculate the distance between the corresponding first edge 121 and the second edge 201.

[0108] In the embodiment, the distance between the first edge 121 and the corresponding second edge 201 is calculated. For example, if the first edge 121 is the edge of a certain side (left side) of the glass substrate 10, then the second edge 201 is the edge corresponding to the first edge 121 on that side (left side), that is, the second edge 201 is the edge of the adhesive layer 20 on that side (left side).

[0109] The calculation module 140 can be used to perform the above-described step S140. For a detailed description of the implementation of the calculation module 140, please refer to the above-described detailed description of step S140.

[0110] The determination module 150 is used to compare the distance with a preset distance threshold. When the distance is greater than or equal to the preset distance threshold, it determines that the distance between the second edge 201 of the adhesive layer 20 and the first edge 121 of the glass substrate 10 is within the preset control specification. When the distance is less than the preset distance threshold, it determines that the distance between the second edge 201 of the adhesive layer 20 and the first edge 121 of the glass substrate 10 is outside the preset control specification.

[0111] The determination module 150 determines whether the distance between the first edge 121 and the corresponding second edge 201 is within a preset control specification by comparing the relationship between the distance and a preset distance threshold. The inventors found that when the distance is not within the preset control specification, the probability of process defects increases. Therefore, in this embodiment, if it is determined that the distance is not within the preset control specification, the position area of ​​the adhesive layer 20 on the glass substrate 10 can be changed by adjusting the adhesive coating parameters so that the distance between the two is within the preset control specification after adjustment.

[0112] The determination module 150 can be used to execute the above-mentioned step S150. For a detailed description of the implementation of the determination module 150, please refer to the above-mentioned detailed description of step S150.

[0113] It should be noted that the division of the various modules in the above system is merely a logical functional division. In actual implementation, they can be fully or partially integrated into a single physical entity, or they can be physically separated. These modules can be implemented entirely in software (e.g., open-source software) through calls from processing elements, or entirely in hardware. Alternatively, some modules can be implemented by processing elements calling software, while others are implemented in hardware. For example, the detection module 130 can be a separate processing element, or it can be integrated into a chip within the system. Furthermore, it can be stored as program code in the system's memory, and its functions can be called and executed by a processing element. The implementation of other modules is similar. These modules can be fully or partially integrated together, or they can be implemented independently. The processing element described here can be an integrated circuit with signal processing capabilities. During implementation, the steps of the above method or the various modules can be completed through integrated logic circuits in the processor element or through software instructions.

[0114] Please refer to Figure 7 , Figure 7A schematic diagram of the hardware structure of a computer device 10 for implementing the above-described adhesive coating detection method is shown in an embodiment of this disclosure. The computer device 10 can be implemented on a cloud server. Figure 7 As shown, the computer device 10 may include a processor 101, a computer-readable storage medium 102, a bus 103, and a communication interface 104.

[0115] In the specific implementation process, at least one processor 101 executes computer execution instructions stored in the computer-readable storage medium 102, so that the processor 101 can execute the adhesive detection method as described in the above method embodiment. The processor 101, the computer-readable storage medium 102, and the communication interface 104 are connected through a bus 103. The processor 101 can be used to control the sending and receiving actions of the communication interface 104.

[0116] The specific implementation process of processor 101 can be found in the various method embodiments executed by the computer device 10 described above. The implementation principle and technical effect are similar, and will not be repeated here.

[0117] The computer-readable storage medium 102 may include high-speed RAM memory and may also include non-volatile storage NVM, such as at least one disk storage.

[0118] Bus 103 can be divided into address bus, data bus, control bus, etc. For ease of illustration, the buses in the accompanying drawings of this invention are not limited to only one bus or one type of bus.

[0119] Furthermore, embodiments of the present invention also provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-described adhesive coating detection method.

[0120] This application provides a method, apparatus, and computer device for detecting adhesive coating. First, a first image of a glass substrate coated with an adhesive layer is acquired. Next, a first edge of the glass substrate and a second edge of the adhesive layer in the first image are identified. Then, the presence of residual adhesive in a target area between the edge of the glass substrate and the edge of the adhesive layer is detected. If residual adhesive is present in the target area, it is marked. This method allows for the detection of residual adhesive in the non-adhesive-coated area between the edge of the glass substrate and the edge of the adhesive layer. This enables timely identification and appropriate processing of glass substrates with residual adhesive, preventing process defects caused by residual adhesive during subsequent manufacturing processes and improving the yield rate of display panels.

[0121] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps described in the claims may be performed in a different order than those shown in the embodiments and may still achieve the desired results. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. A method for detecting adhesive coating, characterized in that, The method includes: A first image of a glass substrate coated with an adhesive layer is obtained, wherein the edges of the glass substrate are all located within the first image; Edge recognition is performed on the first image to identify the first edge of the glass substrate and the second edge of the adhesive layer in the first image; Detect whether there is residual adhesive in the target area between the edge of the glass substrate and the edge of the adhesive layer. If there is residual adhesive in the target area, mark the residual adhesive in the target area.

2. The adhesive coating detection method as described in claim 1, characterized in that, The method further includes: Calculate the distance between the corresponding first edge and the second edge; The distance is compared with a preset distance threshold. If the distance is greater than or equal to the preset distance threshold, it is determined that the distance between the second edge of the adhesive layer and the first edge of the glass substrate is within the preset control specification. If the distance is less than the preset distance threshold, it is determined that the distance between the second edge of the adhesive layer and the first edge of the glass substrate is outside the preset control specification.

3. The adhesive coating detection method as described in claim 2, characterized in that, The step of acquiring a first image of a glass substrate coated with an adhesive layer includes: Acquire images of glass substrates coated with adhesive layers captured by an image acquisition device; The glass substrate image is processed to obtain the first image, wherein the image processing includes noise reduction and grayscale conversion.

4. The adhesive coating detection method as described in claim 3, characterized in that, The step of performing edge recognition on the first image to identify the first edge of the glass substrate and the second edge of the adhesive layer in the first image includes: An edge detection operator is used to calculate the gradient magnitude and gradient direction of pixels in the first image, and a non-maximum suppression method is applied to determine the first edge to be determined of the glass substrate in the first image and the second edge to be determined of the adhesive layer in the first image. The gradient magnitude of each pixel in the first and second edges to be determined is compared with a first gradient magnitude threshold and a second gradient magnitude threshold, respectively, wherein the first gradient magnitude threshold is greater than the second gradient magnitude threshold. When the gradient magnitude of a pixel is greater than or equal to the first gradient magnitude threshold, the pixel is determined to be an edge pixel. When the gradient magnitude of a pixel is less than the first gradient magnitude threshold but greater than or equal to the second gradient magnitude threshold, it is detected whether the pixel is connected to a determined edge pixel. If connected, the pixel is determined to be an edge pixel; otherwise, the pixel is determined to be a non-edge pixel. When the gradient magnitude of a pixel is less than the first gradient magnitude threshold and less than the second gradient magnitude threshold, the pixel is determined to be a non-edge pixel. The first edge is formed by the determined edge pixels in the first edge to be determined, and the second edge is formed by the determined edge pixels in the second edge to be determined.

5. The adhesive coating detection method as described in claim 2, characterized in that, After the step of performing edge recognition on the first image to identify the first edge of the glass substrate and the second edge of the adhesive layer in the first image, the method further includes: The first image after edge recognition is segmented to obtain multiple sub-images; Preferably, the adhesive layer comprises a first adhesive layer and a second adhesive layer stacked on top of each other, and the second edge comprises the edge of the first adhesive layer in the first image and the edge of the second adhesive layer in the first image.

6. The adhesive coating detection method as described in claim 5, characterized in that, The step of detecting whether there is residual adhesive in a target area between the edge of the glass substrate and the edge of the adhesive layer, and marking the residual adhesive in the target area if there is residual adhesive, includes: The first edge of the glass substrate and the second edge of the adhesive layer are identified using a moving average method, forming a mask for identifying the target area between the first edge of the glass substrate and the second edge of the adhesive layer; The mask is used to retain only the image information of the target region in the first image; Detect whether there are pixels in the target area with a gray level value greater than a preset gray level threshold. When there are pixels with a gray level value greater than the preset gray level threshold, determine that there is residual adhesive at the position corresponding to the pixel. The gray level value of the adhesive layer in the first image is greater than the preset gray level threshold. Mark the residual adhesive in the target area; Preferably, when the residual adhesive is present in the target area, the method further includes: The output includes the image name of the sub-image of the residual adhesive and the coordinate position information of the residual adhesive in the corresponding sub-image.

7. The adhesive coating detection method as described in claim 2, characterized in that, The step of calculating the distance between the first edge and the second edge includes: Calculate the number of pixels located between the corresponding first edge and the second edge and arranged along a direction perpendicular to the extension of the first edge or the extension of the second edge, and use the number of pixels as the distance.

8. The adhesive coating detection method as described in claim 7, characterized in that, When the distance between the second edge of the adhesive layer and the first edge of the glass substrate is within a preset control specification, the method further includes: Output the identification information of the glass substrate, the position information of the first edge and the second edge, and the corresponding distance between the first edge and the second edge; Preferably, when the distance between the second edge of the adhesive layer and the first edge of the glass substrate is outside the preset control specification, the method further includes: The output includes the identification information of the glass substrate, the position information of the first edge and the second edge located outside the preset control specifications, and the distance between the first edge and the second edge located outside the preset control specifications.

9. A glue coating detection device, characterized in that, The device includes: An acquisition module is used to acquire a first image of a glass substrate coated with an adhesive layer, wherein the edges of the glass substrate are all located within the first image; The recognition module is used to perform edge recognition on the first image, and to identify the first edge of the glass substrate and the second edge of the adhesive layer in the first image; The detection module is used to detect whether there is residual adhesive in the target area between the edge of the glass substrate and the edge of the adhesive layer. If there is residual adhesive in the target area, the residual adhesive is marked in the target area.

10. A computer device, characterized in that, The computer device includes a processor, a computer-readable storage medium, and a communication interface. The computer-readable storage medium, the communication interface, and the processor are connected via a bus system. The computer-readable storage medium is used to store programs, instructions, or code. The processor is used to execute the programs, instructions, or code in the computer-readable storage medium to perform the adhesive coating detection method according to any one of claims 1-8.

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