Display panel grading method, apparatus, equipment and readable storage medium

Abstract

This invention provides a method, apparatus, device, and readable storage medium for grading display panels. The method includes: acquiring a standard image obtained by photographing the display interface of a standard display panel displaying a preset image; obtaining a reference value based on the standard image; and determining the grading result of the display panel to be graded based on the grayscale values ​​of defect points detected on the display panel to be graded, the reference value, and a preset grading rule. This invention can effectively classify the quality grades of display panels.

Description

Technical Field

[0001] This invention relates to the field of optical inspection technology, and in particular to a method, apparatus, device, and readable storage medium for grading display panels. Background Technology

[0002] Different customers have varying quality requirements for display panels, and even display panels produced on the same production line cannot guarantee completely consistent quality. Therefore, it is necessary to classify the quality of display panels to determine which customers each panel is suitable for delivery to. Based on this, a method for classifying the quality of display panels is urgently needed. Summary of the Invention

[0003] The main objective of this invention is to provide a method, apparatus, device, and readable storage medium for classifying display panels, aiming to solve the technical problem of how to classify the quality grades of display panels.

[0004] In a first aspect, the present invention provides a display panel grading method, the display panel grading method comprising:

[0005] Acquire a standard image by taking a picture of the display interface of a standard display panel that displays a preset image;

[0006] Based on the standard image, a reference value is obtained;

[0007] The grading result of the display panel to be graded is determined based on the grayscale value of the defect points detected on the display panel to be graded, the reference value, and the preset grading rules.

[0008] Optionally, the standard image includes several dot-matrix images arranged in N rows, where N is a positive integer. The step of obtaining the reference value based on the standard image includes:

[0009] Based on the standard image, the three-channel values ​​of each dot image are obtained;

[0010] The three-channel values ​​of each point image are weighted to obtain the weighted value of each point image;

[0011] The reference value for each row is obtained by weighting the point images in the same row.

[0012] Optionally, the step of obtaining the reference value corresponding to each row based on the weighted values ​​of the dotted images in the same row includes:

[0013] Calculate the average weighted value of the dot images in the same row, and use the average weighted value of the dot images in the same row as the reference value for each row.

[0014] Optionally, the standard image includes several clustered images arranged in N rows, where N is a positive integer, and each clustered image is composed of multiple circular images with different grayscale values. The step of obtaining the reference value based on the standard image includes:

[0015] Based on the standard image, obtain the grayscale values ​​of multiple circular images corresponding to each cluster image;

[0016] The gray values ​​of the multiple circular images corresponding to each cluster image are weighted and calculated to obtain the weighted value corresponding to each cluster image;

[0017] The reference value for each row is obtained by weighting the clustered images in the same row.

[0018] Optionally, the step of obtaining the reference value corresponding to each row based on the weighted values ​​corresponding to the clustered images in the same row includes:

[0019] Calculate the average of the weighted values ​​corresponding to the clustered images in the same row, and use the average of the weighted values ​​corresponding to the clustered images in the same row as the reference value for each row.

[0020] Optionally, the step of determining the grading result of the display panel to be graded based on the grayscale values ​​of the defect points detected on the display panel to be graded, the reference value, and the preset grading rules includes:

[0021] Select one unselected defect point from all the defect points detected on the display panel to be graded;

[0022] If the gray value of the defect point is greater than the first reference value corresponding to the first row, then the classification result corresponding to the defect point is determined to be level 1;

[0023] If the gray value of the defect point is less than the i-th reference value corresponding to the i-th row, and there are i+1 defect points within a range with the defect point as the center and the i-th length corresponding to the i-th row as the radius, then the classification result corresponding to the defect point is determined to be level i+1, where the value of i includes positive integers from 1 to N.

[0024] Detect whether there are any unselected defect points;

[0025] If there are unselected defect points, return to the step of selecting an unselected defect point from all defect points detected on the display panel to be graded;

[0026] When there are no unselected defect points, the grading result of the display panel to be graded is determined based on all grading results corresponding to all defect points.

[0027] Optionally, the step of determining the grading result of the display panel to be graded based on all grading results corresponding to all defect points includes:

[0028] Select the lowest grade from all the grading results corresponding to all defect points as the grading result of the display panel to be graded, wherein the grade of grade i is less than the grade of grade i+1.

[0029] In a second aspect, the present invention also provides a display panel grading device, the display panel grading device comprising:

[0030] The acquisition module is used to acquire a standard image obtained by capturing a standard display panel that displays a preset image.

[0031] A reference value determination module is used to obtain reference values ​​based on the standard image;

[0032] The grading module is used to determine the grading result of the display panel to be graded based on the grayscale value of the defect points detected on the display panel to be graded, the reference value, and the preset grading rules.

[0033] Thirdly, the present invention also provides a display panel grading device, the display panel grading device including a processor, a memory, and a display panel grading program stored in the memory and executable by the processor, wherein when the display panel grading program is executed by the processor, it implements the steps of the display panel grading method as described above.

[0034] Fourthly, the present invention also provides a readable storage medium storing a display panel grading program, wherein when the display panel grading program is executed by a processor, it implements the steps of the display panel grading method as described above.

[0035] In this invention, a standard image is obtained by capturing a photograph of the display interface of a standard display panel displaying a preset image; a reference value is obtained based on the standard image; and the grading result of the display panel to be graded is determined based on the grayscale values ​​of defect points detected on the display panel to be graded, the reference value, and the preset grading rules. This invention effectively classifies the quality levels of display panels. Attached Figure Description

[0036] Figure 1 This is a flowchart illustrating an embodiment of the display panel grading method of the present invention;

[0037] Figure 2 This is a schematic diagram of a preset image in one embodiment of the display panel grading method of the present invention;

[0038] Figure 3This is a schematic diagram of a clustered image in one embodiment of the display panel grading method of the present invention;

[0039] Figure 4 As one embodiment Figure 1 A detailed flowchart of step S20;

[0040] Figure 5 This is a schematic diagram illustrating the calculation results of the three-channel values ​​of each dot image in one embodiment;

[0041] Figure 6 In another embodiment Figure 1 A detailed flowchart of step S20;

[0042] Figure 7 As one embodiment Figure 1 A detailed flowchart of step S30;

[0043] Figure 8 This is a functional module diagram of an embodiment of the display panel grading device of the present invention;

[0044] Figure 9 This is a schematic diagram of the hardware structure of the display panel grading device involved in the embodiment of the present invention.

[0045] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0046] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0047] In a first aspect, embodiments of the present invention provide a method for classifying display panels.

[0048] In one embodiment, reference is made to Figure 1 , Figure 1 This is a schematic flowchart of an embodiment of the display panel grading method of the present invention. Figure 1 As shown, the display panel grading method includes:

[0049] Step S10: Obtain a standard image by taking a picture of the display interface of a standard display panel displaying a preset image;

[0050] In this embodiment, a preset image is displayed on a standard display panel, and then a camera is used to capture an image of the display interface of the standard display panel displaying the preset image, thereby obtaining the standard image captured by the camera. Here, a standard display panel refers to a display panel of excellent quality.

[0051] The preset image is set according to actual needs. For example, the preset image includes several dot images, and the three-channel values ​​(RGB three-channel values) of each dot image are preset values. These dot images are arranged in N rows, and the value of N is set according to actual needs. (Refer to...) Figure 2 , Figure 2 This is a schematic diagram of a preset image in one embodiment of the display panel grading method of the present invention. Figure 2 As shown, 15 dot images are arranged in 4 rows. It should be noted that this is only an illustrative illustration of the preset images and does not constitute a limitation on the preset images. In actual implementation, the preset number of dot images can be set according to actual needs, and the number of dot images included in each row can also be set according to actual needs.

[0052] For example, the preset image includes several clustered images arranged in N rows, and the arrangement can be referenced. Figure 2 . Reference Figure 3 , Figure 3 This is a schematic diagram of a clustered image in one embodiment of the display panel grading method of the present invention. Figure 3 As shown, the clumped image is composed of multiple different circular images. The grayscale value of each circular image is a preset value. It should be noted that this is only an illustrative description of the clumped image and does not constitute a limitation on it. In actual implementation, the number of circular images can be set according to actual needs and is not limited to the three in this embodiment.

[0053] It is easy to understand that the obtained standard image includes the aforementioned preset image.

[0054] Step S20: Obtain reference values ​​based on the standard image;

[0055] In this embodiment, a preset image in the standard image is analyzed to obtain a reference value.

[0056] Furthermore, in one embodiment, the standard image comprises several dot-like images arranged in N rows, where N is a positive integer, as shown below. Figure 4 , Figure 4 As one embodiment Figure 1 A detailed flowchart of step S20. (See attached diagram.) Figure 4 As shown, step S20 includes:

[0057] Step S201: Obtain the three-channel values ​​of each dot image based on the standard image;

[0058] In this embodiment, refer to Figure 2 It is easy to understand that when the preset image is like... Figure 2As shown, the captured step image also includes several point images arranged in N rows, where N is a positive integer. Each point image in the standard image can then be analyzed to obtain its three-channel values. (Refer to...) Figure 5 , Figure 5 This is a schematic diagram illustrating the calculation results of the three-channel values ​​of various point images in one embodiment.

[0059] Step S202: Perform weighted calculation on the three-channel values ​​of each point image to obtain the weighted value of each point image;

[0060] In this embodiment, as Figure 5 As shown, the three-channel values ​​of the dot image located in the first row and first column are (R11, G11, B11). Therefore, the weighted value of the dot image located in the first row and first column is Q11 = R11*x + G11*y + B11*z, where x, y, and z are preset weight factors, and x + y + z = 1. Similarly, the weighted value of the dot image located in the first row and second column is Q12 = R12*x + G12*y + B12*z, where x, y, and z are preset weight factors, and x + y + z = 1. Likewise, the weighted value of the dot image located in the first row and third column is Q13 = R13*x + G13*y + B13*z, where x, y, and z are preset weight factors, and x + y + z = 1. This process continues to obtain the weighted values ​​for each dot image.

[0061] Step S203: Obtain the reference value corresponding to each row based on the weighted values ​​of the dotted images in the same row.

[0062] In this embodiment, taking the dotted image in the first row as an example, the reference value corresponding to the first row can be obtained according to Q11, Q12, and Q13. Specifically, the maximum and minimum values ​​of the weighted values ​​of the dotted images in the same row can be removed, and then the average value is calculated as the reference value for the corresponding row. Of course, other methods can be used to determine the reference value, and this is not limited here.

[0063] Further, in one embodiment, step S203 includes:

[0064] Calculate the average weighted value of the dot images in the same row, and use the average weighted value of the dot images in the same row as the reference value for each row.

[0065] In this embodiment, taking the dotted image in the first row as an example, P1 = (Q11 + Q12 + Q13) / 3 is calculated, and P1 is used as the reference value for the first row. Similarly, the reference values ​​for each of the other rows can be calculated.

[0066] Further, in one embodiment, the standard image includes several clustered images arranged in N rows, where N is a positive integer, and each clustered image is composed of multiple circular images with different grayscale values, as shown in the figure. Figure 6 , Figure 6 In another embodiment Figure 1 A detailed flowchart of step S20. (See attached diagram.) Figure 6 As shown, step S20 includes:

[0067] Step S204: Based on the standard image, obtain the grayscale values ​​of multiple circular images corresponding to each cluster image;

[0068] In this embodiment, the set Figure 2 and Figure 3 Soon Figure 2 Replace the dotted image in Figure 3 The standard image contains clumped images. Each clumped image in the standard image is analyzed to obtain the grayscale values ​​of multiple circular images corresponding to each clumped image.

[0069] Step S205: Perform weighted calculation on the gray values ​​of multiple circular images corresponding to each cluster image to obtain the weighted value corresponding to each cluster image;

[0070] In this embodiment, taking a certain clustered image as an example, the gray values ​​from the inner circle to the outer circle are G1, G2, and G3, respectively. The weight factors for each clustered image are preset values, namely P1, P2, and P3, and P1 + P2 + P3 = 1. Therefore, the weighted value corresponding to the clustered image is G1*P1 + G2*P2 + G3*P3. This process can be repeated to obtain the weighted value corresponding to each clustered image.

[0071] Step S206: Obtain the reference value for each row based on the weighted values ​​corresponding to the clustered images in the same row.

[0072] In this embodiment, the maximum and minimum values ​​of the weighted values ​​of clustered images in the same row can be removed, and then the average value can be calculated as the reference value for the corresponding row. Of course, other methods can be selected to determine the reference value, and there are no restrictions here.

[0073] Further, in one embodiment, step S206 includes:

[0074] Calculate the average of the weighted values ​​corresponding to the clustered images in the same row, and use the average of the weighted values ​​corresponding to the clustered images in the same row as the reference value for each row.

[0075] In this embodiment, assuming the first row includes three clustered images with weighted values ​​of GL1, GL2, and GL3, the reference value for the first row is (GL1 + GL2 + GL3) / 3. This pattern continues to yield the reference value for each row.

[0076] Step S30: Determine the grading result of the display panel to be graded based on the grayscale value of the defect point detected on the display panel to be graded, the reference value, and the preset grading rules.

[0077] In this embodiment, defect points on the display panel to be graded are identified by performing defect detection, and the grayscale values ​​of the defect points are obtained. The grayscale values ​​of the defect points are compared with reference values ​​to obtain the comparison results. Then, combined with preset grading rules, the grading result of the display panel to be graded is determined. The preset grading rules are set according to actual conditions.

[0078] In this embodiment, a standard image is obtained by capturing a picture of the display interface of a standard display panel displaying a preset image; a reference value is obtained based on the standard image; and the grading result of the display panel to be graded is determined based on the grayscale values ​​of defect points detected on the display panel to be graded, the reference value, and the preset grading rules. This embodiment effectively classifies the quality levels of display panels.

[0079] Furthermore, in one embodiment, reference is made to Figure 7 , Figure 7 As one embodiment Figure 1 A detailed flowchart of step S30. (See attached diagram.) Figure 7 As shown, step S30 includes:

[0080] Step S301: Select an unselected defect point from all the defect points detected on the display panel to be graded;

[0081] In this embodiment, it is easy to understand that there are usually multiple defect points detected on the display panel to be graded, and one unselected defect point is chosen from among the multiple defect points. For example, the defect points include defect point 1 to defect point 5, and defect point 1 is selected first.

[0082] Step S302: If the gray value of the defect point is greater than the first reference value corresponding to the first row, then the classification result corresponding to the defect point is determined to be level 1; if the gray value of the defect point is less than the i-th reference value corresponding to the i-th row, and there are i+1 defect points within a range with the defect point as the center and the i-th length corresponding to the i-th row as the radius, then the classification result corresponding to the defect point is determined to be level i+1, where the value of i includes positive integers from 1 to N;

[0083] In this embodiment, the gray value of defect point 1 is compared with the first reference value corresponding to the first row. If the gray value of defect point 1 is greater than the first reference value corresponding to the first row, the classification result corresponding to defect point 1 is determined to be level 1.

[0084] If the gray value of a defect point is less than the first reference value corresponding to the first row, and there are two defect points within a range with defect point 1 as the center and the first length corresponding to the first row as the radius, then the classification result corresponding to defect point 1 is determined to be level 2.

[0085] Similarly, if the gray value of a defect point is less than the second reference value corresponding to the second row, and there are 3 defect points within a radius of the second length corresponding to the second row with defect point 1 as the center, then the classification result corresponding to defect point 1 is determined to be level 3.

[0086] By analogy, the classification result corresponding to defect point 1 can be obtained.

[0087] The length of the i-th row is set according to actual needs. For example, the first length of the first row is 10 pixels, and the second length of the second row is 15 pixels. This is for illustrative purposes only and does not constitute a limitation on this embodiment.

[0088] Step S303: Detect whether there are any unselected defect points;

[0089] If there are unselected defect points, return to step S301;

[0090] Step S304: When there are no unselected defect points, determine the grading result of the display panel to be graded based on all grading results corresponding to all defect points.

[0091] In this embodiment, if there are unselected defect points, the process returns to step S301, thus obtaining the grading results corresponding to each defect point. Finally, the grading result of the display panel to be graded is determined by combining all grading results corresponding to all defect points.

[0092] Further, in one embodiment, step S304 includes:

[0093] Select the lowest grade from all the grading results corresponding to all defect points as the grading result of the display panel to be graded, wherein the grade of grade i is less than the grade of grade i+1.

[0094] In this embodiment, the lower the grade, the lower the quality of the display panel. Therefore, the lowest grade is selected from all the grading results corresponding to all defect points as the grading result of the display panel to be graded.

[0095] Secondly, embodiments of the present invention also provide a display panel grading device.

[0096] In one embodiment, reference is made to Figure 8 , Figure 8 This is a functional module diagram of an embodiment of the display panel grading device of the present invention. Figure 8 As shown, the display panel grading device includes:

[0097] The acquisition module 10 is used to acquire a standard image obtained by capturing a standard display panel displaying a preset image.

[0098] Reference value determination module 20 is used to obtain reference values ​​based on the standard image;

[0099] The grading module 30 is used to determine the grading result of the display panel to be graded based on the grayscale value of the defect point detected on the display panel to be graded, the reference value, and the preset grading rules.

[0100] Further, in one embodiment, the standard image includes several dot-like images arranged in N rows, where N is a positive integer. The reference value determination module 20 is used for:

[0101] Based on the standard image, the three-channel values ​​of each dot image are obtained;

[0102] The three-channel values ​​of each point image are weighted to obtain the weighted value of each point image;

[0103] The reference value for each row is obtained by weighting the point images in the same row.

[0104] Furthermore, in one embodiment, the reference value determination module 20 is used for:

[0105] Calculate the weighted average of the point images in the same row, using the point images in the same row as the average. Figure 5 The average of the weighted values ​​of the images is used as the reference value for each row.

[0106] Further, in one embodiment, the standard image includes several clustered images arranged in N rows, where N is a positive integer, and each clustered image is composed of multiple circular images with different grayscale values. The reference value determination module 20 is used for:

[0107] Based on the standard image, the grayscale values ​​of multiple circular images corresponding to each cluster image are obtained; 0 weights the grayscale values ​​of the multiple circular images corresponding to each cluster image to obtain each

[0108] The weighted values ​​corresponding to the clumped image;

[0109] The reference value for each row is obtained by weighting the clustered images in the same row.

[0110] Furthermore, in one embodiment, the reference value determination module 20 is used for...

[0111] Calculate the average of the weighted values ​​corresponding to the clustered images in the same row, and use the average of the weighted values ​​corresponding to the clustered images in the same row as the reference value for each row.

[0112] Furthermore, in one embodiment, the hierarchical module 30 is used for:

[0113] Select one unselected defect point from all the defect points detected on the display panel to be graded;

[0114] If the gray value of the defect point is greater than the first reference value corresponding to the first row, then the classification result corresponding to the defect point 0 is determined to be level 1;

[0115] If the gray value of the defect point is less than the i-th reference value corresponding to the i-th row, and there are i+1 defect points within a range with the defect point as the center and the i-th length corresponding to the i-th row as the radius, then the classification result corresponding to the defect point is determined to be level i+1, where the value of i includes positive integers from 1 to N.

[0116] Detect whether there are any unselected defect points;

[0117] 5. If there are unselected defect points, return to the step of selecting an unselected defect point from all defect points detected on the display panel to be graded;

[0118] When there are no unselected defect points, the grading result of the display panel to be graded is determined based on all grading results corresponding to all defect points.

[0119] Furthermore, in one embodiment, the grading module 30 is used to: select the lowest grade grading result from all grading results corresponding to all defect points as the grading result of the display panel to be graded, wherein the grade of grade i is less than grade i+1.

[0120] The functions of each module in the above-mentioned display panel grading device correspond to the steps in the above-mentioned display panel grading method embodiment, and their functions and implementation processes will not be described in detail here.

[0121] Thirdly, embodiments of the present invention provide a display panel grading device, which can be a device with data processing capabilities such as a personal computer (PC), a laptop computer, or a server.

[0122] Reference Figure 9 , Figure 9This is a schematic diagram of the hardware structure of the display panel grading device involved in an embodiment of the present invention. In this embodiment, the display panel grading device may include a processor 1001 (e.g., a Central Processing Unit, CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. The communication bus 1002 is used to realize communication between these components; the user interface 1003 may include a display screen and an input unit such as a keyboard; the network interface 1004 may optionally include a standard wired interface or a wireless interface (e.g., Wireless Fidelity, Wi-Fi); the memory 1005 may be high-speed random access memory (RAM) or stable memory (non-volatile memory), such as a disk storage device. The memory 1005 may also optionally be a storage device independent of the aforementioned processor 1001. Those skilled in the art will understand that… Figure 9 The hardware structure shown does not constitute a limitation of the invention and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0123] Continue to refer to Figure 9 , Figure 9 The memory 1005, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and a display panel classification program. The processor 1001 can call the display panel classification program stored in the memory 1005 and execute the display panel classification method provided in this embodiment of the invention.

[0124] Fourthly, embodiments of the present invention also provide a readable storage medium.

[0125] The present invention provides a display panel grading program stored on a readable storage medium, wherein when the display panel grading program is executed by a processor, it implements the steps of the display panel grading method described above.

[0126] The method implemented when the display panel grading procedure is executed can be referred to in various embodiments of the display panel grading method of the present invention, and will not be repeated here.

[0127] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0128] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0129] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a terminal device to execute the methods described in the various embodiments of the present invention.

[0130] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A method for grading display panels, characterized in that, The display panel grading method includes: Acquire a standard image by taking a picture of the display interface of a standard display panel that displays a preset image; Based on the standard image, a reference value is obtained; The grading result of the display panel to be graded is determined based on the grayscale value of the defect points detected on the display panel to be graded, the reference value, and the preset grading rules. The standard image includes several dot-like or cluster-like images, arranged in N rows, where N is a positive integer, and the reference value is the reference value corresponding to each row of the standard image; The step of determining the grading result of the display panel to be graded based on the grayscale values ​​of the defect points detected on the display panel to be graded, the reference values, and the preset grading rules includes: Select one unselected defect point from all the defect points detected on the display panel to be graded; If the gray value of the defect point is greater than the first reference value corresponding to the first row, then the classification result corresponding to the defect point is determined to be level 1; If the gray value of the defect point is less than the i-th reference value corresponding to the i-th row, and there are i+1 defect points within a range with the defect point as the center and the i-th length corresponding to the i-th row as the radius, then the classification result corresponding to the defect point is determined to be level i+1, where the value of i includes positive integers from 1 to N. Detect whether there are any unselected defect points; If there are unselected defect points, return to the step of selecting an unselected defect point from all defect points detected on the display panel to be graded; When there are no unselected defect points, the grading result of the display panel to be graded is determined based on all grading results corresponding to all defect points.

2. The display panel grading method as described in claim 1, characterized in that, The standard image comprises several dot-like images arranged in N rows, where N is a positive integer. The step of obtaining reference values ​​based on the standard image includes: Based on the standard image, the three-channel values ​​of each dot image are obtained; The three-channel values ​​of each point image are weighted to obtain the weighted value of each point image; The reference value for each row is obtained by weighting the point images in the same row.

3. The display panel grading method as described in claim 2, characterized in that, The step of obtaining the reference value corresponding to each row based on the weighted values ​​of the dotted images in the same row includes: Calculate the average weighted value of the dot images in the same row, and use the average weighted value of the dot images in the same row as the reference value for each row.

4. The display panel grading method as described in claim 1, characterized in that, The standard image comprises several clustered images arranged in N rows, where N is a positive integer, and each clustered image is composed of multiple circular images with different grayscale values. The step of obtaining reference values ​​based on the standard image includes: Based on the standard image, obtain the grayscale values ​​of multiple circular images corresponding to each cluster image; The gray values ​​of the multiple circular images corresponding to each cluster image are weighted and calculated to obtain the weighted value corresponding to each cluster image; The reference value for each row is obtained by weighting the clustered images in the same row.

5. The display panel grading method as described in claim 4, characterized in that, The step of obtaining the reference value for each row based on the weighted values ​​corresponding to the clustered images in the same row includes: Calculate the average of the weighted values ​​corresponding to the clustered images in the same row, and use the average of the weighted values ​​corresponding to the clustered images in the same row as the reference value for each row.

6. The display panel grading method as described in claim 1, characterized in that, The step of determining the grading result of the display panel to be graded based on all grading results corresponding to all defect points includes: Select the lowest grade from all the grading results corresponding to all defect points as the grading result of the display panel to be graded, wherein the grade of grade i is less than the grade of grade i+1.

7. A display panel grading device, characterized in that, The display panel grading device includes: The acquisition module is used to acquire a standard image obtained by capturing a standard display panel that displays a preset image. A reference value determination module is used to obtain reference values ​​based on the standard image; The grading module is used to determine the grading result of the display panel to be graded based on the grayscale value of the defect points detected on the display panel to be graded, the reference value, and the preset grading rules. The standard image includes several dot-like or cluster-like images, arranged in N rows, where N is a positive integer, and the reference value is the reference value corresponding to each row of the standard image; The grading module is also used to select an unselected defect point from all the defect points detected on the display panel to be graded; If the gray value of the defect point is greater than the first reference value corresponding to the first row, then the classification result corresponding to the defect point is determined to be level 1; If the gray value of the defect point is less than the i-th reference value corresponding to the i-th row, and there are i+1 defect points within a range with the defect point as the center and the i-th length corresponding to the i-th row as the radius, then the classification result corresponding to the defect point is determined to be level i+1, where the value of i includes positive integers from 1 to N. Detect whether there are any unselected defect points; If there are unselected defect points, return to the step of selecting an unselected defect point from all defect points detected on the display panel to be graded; When there are no unselected defect points, the grading result of the display panel to be graded is determined based on all grading results corresponding to all defect points.

8. A display panel grading device, characterized in that, The display panel grading device includes a processor, a memory, and a display panel grading program stored in the memory and executable by the processor, wherein when the display panel grading program is executed by the processor, it implements the steps of the display panel grading method as described in any one of claims 1 to 6.

9. A readable storage medium, characterized in that, The readable storage medium stores a display panel grading program, wherein when the display panel grading program is executed by a processor, it implements the steps of the display panel grading method as described in any one of claims 1 to 6.

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