A detection method, device and system for a display panel

Abstract

The present disclosure provides a detection method, device and system for a display panel (100, 200), wherein the detection method includes: S101: obtaining a to-be-detected image of the display panel (100, 200) including a special-shaped area; S102: calculating the position coordinates of an ink area from the to-be-detected image; S103: determining a defect detection area in the to-be-detected image according to the coordinate position of the ink area; S104: determining a defective defect in the to-be-detected image by statistically analyzing the feature information of a plurality of pixel points in the defect detection area.

Description

Technical Field

[0001] The present disclosure relates to the field of display technologies, and particularly to a method, apparatus, and system for detecting a display panel. Background Art

[0002] In the process of manufacturing a flexible active-matrix organic light-emitting diode (AMOLED) display panel, it is often necessary to bond a flexible AMOLED display device to a cover plate. During the bonding process, defects such as bubbles and stains are likely to occur between the two, thereby affecting the display quality of the flexible AMOLED display panel.

[0003] Existing defect detection mainly uses manual detection methods. Specifically, the flexible AMOLED display panel is detected by the naked eye, and the entire detection process is prone to missed detection and over-detection.

[0004] It can be seen that the existing defect detection has the technical problem of low detection efficiency. Summary of the Invention

[0005] The present disclosure provides a method, apparatus, and system for detecting a display panel. The specific solutions are as follows:

[0006] An embodiment of the present disclosure provides a method for detecting a display panel, which includes:

[0007] Obtain a to-be-detected image of the display panel including a special-shaped area;

[0008] Calculate the position coordinates of an ink area from the to-be-detected image;

[0009] Determine a defect detection area in the to-be-detected image according to the coordinate position of the ink area;

[0010] Determine a defective defect in the to-be-detected image by statistically analyzing the feature information of multiple pixel points in the defect detection area.

[0011] Optionally, in an embodiment of the present disclosure, the calculating the position coordinates of the ink area from the to-be-detected image includes:

[0012] Perform binarization processing on the to-be-detected image according to a first threshold;

[0013] Determine the coordinate position of the ink area according to the coordinates of white pixel points in the to-be-detected image after binarization processing according to the first threshold.

[0014] Optionally, in an embodiment of the present disclosure, before calculating the position coordinates of the ink area from the to-be-detected image, the method further includes:

[0015] Perform compression processing, median filtering, and image deep copy processing on the image to be detected.

[0016] Optionally, in the embodiments of the present disclosure, determining the coordinate position of the ink area according to the coordinates of the white pixel points in the image to be detected after binarization processing according to the first threshold includes:

[0017] In the image coordinate system, obtain the ordinate range of the ink area from the image to be detected after binarization processing according to the first threshold, where the ordinate range includes a starting ordinate and an ending ordinate;

[0018] Calculate a first abscissa array at the starting ordinate of the ink area, a second abscissa array at the ending ordinate, and a third abscissa array at a preset coordinate position between the starting ordinate and the ending ordinate;

[0019] Determine the first abscissa-ordinate range where the ink area is located according to the starting ordinate, the first abscissa array, the ending ordinate, the second abscissa array, the preset coordinate position, and the third abscissa array;

[0020] Use the first abscissa-ordinate range as the coordinate position of the ink area in the image coordinate system.

[0021] Optionally, in the embodiments of the present disclosure, after calculating the position coordinates of the ink area from the image to be detected, the method further includes:

[0022] Perform binarization processing on the image to be detected according to a second threshold;

[0023] Determine the position coordinates of the reflective area according to the coordinates of the white pixel points in the image to be detected after binarization processing according to the second threshold and the coordinate position of the ink area;

[0024] Determining the defect detection area in the image to be detected according to the coordinate position of the ink area includes:

[0025] Determine the defect detection area in the image to be detected according to the coordinate position of the ink area and the position coordinates of the reflective area.

[0026] Optionally, in the embodiments of the present disclosure, determining the position coordinates of the reflective area according to the coordinates of the white pixel points in the image to be detected after binarization processing according to the second threshold and the coordinate position of the ink area includes:

[0027] From the coordinates of the white pixel points in the to-be-detected image after binarization according to the second threshold, excluding the coordinate positions of the ink areas, calculate multiple pixel points that are located in the same connected domain and simultaneously satisfy that the ordinate is less than the starting ordinate and greater than the first preset number;

[0028] Determine the second horizontal and vertical coordinate ranges of the connected domain in the image coordinate system;

[0029] Take the second horizontal and vertical coordinate ranges as the coordinate positions of the reflective area in the image coordinate system.

[0030] Optionally, in the embodiments of the present disclosure, the determining the bad defects in the to-be-detected image by statistically analyzing the feature information of multiple pixel points in the defect detection area includes:

[0031] Re-obtain the to-be-detected image, and sequentially perform grayscale processing, median filtering processing, same-scale reduction processing, and binarization processing according to the third threshold on the to-be-detected image;

[0032] Determine the bad defects in the to-be-detected image by statistically analyzing the feature information of multiple pixel points in the defect detection area after binarization according to the third threshold.

[0033] Optionally, in the embodiments of the present disclosure, the determining the bad defects in the to-be-detected image by statistically analyzing the feature information of multiple pixel points in the defect detection area after binarization according to the third threshold includes:

[0034] Statistically analyze at least one set of pixel points from the multiple pixel points in the defect detection area after binarization according to the third threshold, where the pixel points in the set of pixel points have the same grayscale value and are located in the same connected domain;

[0035] Calculate the number of pixel points in each set of pixel points;

[0036] Take the connected domain where the set of pixel points with the number of pixel points greater than the second preset number is located as the bad defect area in the to-be-detected image.

[0037] Optionally, in the embodiments of the present disclosure, after taking the connected domain where the set of pixel points with the number of pixel points greater than the second preset number is located as the bad defect area in the to-be-detected image, the method further includes:

[0038] Mark the connected domain where the set of pixel points is located to indicate that there are bad defects at the corresponding positions of the display panel and the bad defect area in the to-be-detected image.

[0039] Optionally, in the embodiments of the present disclosure, before binarizing the image to be detected according to the first threshold, the method further includes:

[0040] Performing a proportional reduction process on the image to be detected to obtain a reduced image;

[0041] Performing median filtering on the reduced image to obtain a filtered image, and using the filtered image as the image to be detected.

[0042] Correspondingly, the embodiments of the present disclosure provide a detection device for a display panel, which includes:

[0043] An acquisition unit, configured to acquire a to-be-detected image of the display panel including an irregular shape;

[0044] A calculation unit, configured to calculate the position coordinates of the ink area from the to-be-detected image;

[0045] A first determination unit, configured to determine a defect detection area in the to-be-detected image according to the coordinate position of the ink area;

[0046] A second determination unit, configured to determine a bad defect in the to-be-detected image by statistically analyzing the feature information of multiple pixel points in the defect detection area.

[0047] Optionally, in the embodiments of the present disclosure, the calculation unit is configured to:

[0048] Binarize the to-be-detected image according to the first threshold;

[0049] Determine the coordinate position of the ink area according to the coordinates of the white pixel points in the to-be-detected image after binarization according to the first threshold.

[0050] Optionally, in the embodiments of the present disclosure, before the calculation unit calculates the position coordinates of the ink area from the to-be-detected image, the device further includes a preprocessing unit, and the preprocessing unit is configured to:

[0051] Perform compression processing, median filtering, and image deep copy processing on the to-be-detected image.

[0052] Optionally, in the embodiments of the present disclosure, the calculation unit is configured to:

[0053] In the image coordinate system, obtain the ordinate range of the ink area from the to-be-detected image after binarization according to the first threshold, where the ordinate range includes a starting ordinate and an ending ordinate;

[0054] Calculate a first abscissa array of the ink area at the starting ordinate, a second abscissa array of the ink area at the ending ordinate, and a third abscissa array of the ink area at a preset coordinate position between the starting ordinate and the ending ordinate;

[0055] Determine a first range of abscissa and ordinate where the ink area is located according to the starting ordinate, the first abscissa array, the ending ordinate, the second abscissa array, the preset coordinate position, and the third abscissa array;

[0056] Use the first range of abscissa and ordinate as the coordinate position of the ink area in the image coordinate system.

[0057] Optionally, in an embodiment of the present disclosure, after the calculation unit calculates the position coordinates of the ink area from the image to be detected, the calculation unit is further configured to:

[0058] Perform binarization processing on the image to be detected according to a second threshold;

[0059] Determine the position coordinates of the reflective area according to the coordinates of the white pixel points in the image to be detected after binarization processing according to the second threshold and the coordinate position of the ink area;

[0060] The first determination unit is configured to: determine a defect detection area in the image to be detected according to the coordinate position of the ink area and the position coordinates of the reflective area;

[0061] The calculation unit is configured to:

[0062] Excluding the coordinate position of the ink area from the coordinates of the white pixel points in the image to be detected after binarization processing according to the second threshold, calculate a plurality of pixel points located in the same connected domain and simultaneously satisfying that the ordinate is less than the starting ordinate and greater than a first preset number;

[0063] Determine a second range of abscissa and ordinate of the connected domain in the image coordinate system;

[0064] Use the second range of abscissa and ordinate as the coordinate position of the reflective area in the image coordinate system.

[0065] Optionally, in an embodiment of the present disclosure, the second determination unit is configured to:

[0066] Re-obtain the image to be detected, and sequentially perform grayscale processing, median filtering processing, same-scale reduction processing, and binarization processing on the image to be detected according to a third threshold;

[0067] Determine the defective defects in the image to be detected by statistically analyzing the feature information of multiple pixel points in the defect detection area after binarization processing according to the third threshold.

[0068] Optionally, in the embodiments of the present disclosure, the second determination unit is configured to:

[0069] Statistically analyze at least one set of pixel points from multiple pixel points in the defect detection area after binarization processing according to the third threshold, where the pixel points in the set of pixel points have the same gray value and are located in the same connected domain;

[0070] Calculate the number of pixel points in each set of pixel points;

[0071] Regard the connected domain where the set of pixel points with the number of pixel points greater than the second preset number is located as the defective defect area in the image to be detected.

[0072] Optionally, in the embodiments of the present disclosure, the device further includes a marking unit, and the marking unit is configured to:

[0073] Mark the connected domain where the set of pixel points is located to indicate that there are defective defects at the corresponding position of the display panel and the defective defect area in the image to be detected.

[0074] Optionally, in the embodiments of the present disclosure, the device further includes an image processing unit, and the image processing unit is configured to:

[0075] Perform a same-scale reduction process on the image to be detected to obtain a reduced image;

[0076] Perform median filtering on the reduced image to obtain a filtered image, and use the filtered image as the image to be detected.

[0077] Correspondingly, the embodiments of the present disclosure provide a detection system for a display panel, which includes:

[0078] A stage configured to place the display panel;

[0079] An image acquisition unit configured to acquire a to-be-detected image of the display panel including a special-shaped area;

[0080] An industrial control computer configured to obtain the to-be-detected image of the display panel including the special-shaped area from the image acquisition unit; calculate the position coordinates of the ink area from the to-be-detected image; determine the defect detection area in the to-be-detected image according to the coordinate position of the ink area; and determine the defective defects in the to-be-detected image by statistically analyzing the feature information of multiple pixel points in the defect detection area.

[0081] Optionally, in the embodiments of the present disclosure, the image acquisition unit may be one or more, and each image acquisition unit is a line scan camera.

[0082] Correspondingly, the embodiments of the present disclosure provide a detection device for a display panel, which includes:

[0083] A memory and a processor;

[0084] Wherein, the memory is used to store a computer program;

[0085] The processor is used to execute the computer program in the memory to implement the following steps:

[0086] Obtain a to-be-detected image of the display panel including a special-shaped area;

[0087] Calculate the position coordinates of the ink area from the to-be-detected image;

[0088] Determine a defect detection area in the to-be-detected image according to the coordinate position of the ink area;

[0089] Determine a defective defect in the to-be-detected image by statistically analyzing the feature information of multiple pixel points in the defect detection area.

[0090] Correspondingly, the embodiments of the present disclosure provide a computer non-transitory readable storage medium, wherein:

[0091] The storage medium stores computer instructions, and when the computer instructions run on a computer, the computer is caused to execute the detection method of the display panel as described above. Description of the Drawings

[0092] Figure 1 It is a flowchart of a detection method for a display panel provided by an embodiment of the present disclosure;

[0093] Figure 2 It is a flowchart of step S102 in the detection method for a display panel provided by an embodiment of the present disclosure;

[0094] Figure 3 It is one of the schematic diagrams of the to-be-detected image in the detection method for a display panel provided by an embodiment of the present disclosure;

[0095] Figure 4 It is a flowchart of step S202 in the detection method for a display panel provided by an embodiment of the present disclosure;

[0096] Figure 5 It is one of the schematic diagrams of the to-be-detected image in the detection method for a display panel provided by an embodiment of the present disclosure;

[0097] Figure 6 The flowchart of the method after step S102 in a display panel detection method provided by an embodiment of the present disclosure;

[0098] Figure 7 The flowchart of step S402 in a display panel detection method provided by an embodiment of the present disclosure;

[0099] Figure 8 The flowchart of step S104 in a display panel detection method provided by an embodiment of the present disclosure;

[0100] Figure 9 The flowchart of step S602 in a display panel detection method provided by an embodiment of the present disclosure;

[0101] Figure 10 The flowchart of the method before step S102 in a display panel detection method provided by an embodiment of the present disclosure;

[0102] Figure 11 One of the structural block diagrams of a display panel detection device provided by an embodiment of the present disclosure;

[0103] Figure 12 One of the structural block diagrams of a display panel detection system provided by an embodiment of the present disclosure;

[0104] Figure 13 One of the structural schematic diagrams when there are three image acquisition units in a display panel detection system provided by an embodiment of the present disclosure;

[0105] Figure 14 One of the structural schematic diagrams of a display panel detection device provided by an embodiment of the present disclosure. Detailed implementation manners

[0106] To make the objectives, technical solutions and advantages of the embodiments of the present disclosure clearer, the technical solutions of the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present disclosure. Obviously, the described embodiments are some, but not all, of the embodiments of the present disclosure. And without conflict, the embodiments in the present disclosure and the features in the embodiments can be combined with each other. All other embodiments obtained by those of ordinary skill in the art based on the described embodiments of the present disclosure without creative efforts shall fall within the scope of protection of the present disclosure.

[0107] Unless otherwise defined, technical terms or scientific terms used in this disclosure shall have the ordinary meanings understood by those of ordinary skill in the art to which this disclosure pertains. The words such as "including" or "comprising" used in this disclosure mean that the elements or objects appearing before this word cover the elements or objects listed after this word and their equivalents, without excluding other elements or objects.

[0108] In the prior art, the method of manual inspection is mainly adopted to detect defects in the display panel. The entire inspection process is prone to missed inspections and over-inspections. That is to say, there is a technical problem of low defect detection efficiency in the existing technology.

[0109] In view of this, the embodiments of this disclosure provide a detection method, device and system for a display panel, which are used to improve the defect detection efficiency and ensure the display quality of the display panel.

[0110] As Figure 1 shown, a detection method for a display panel provided by an embodiment of this disclosure includes:

[0111] S101: Obtain a to-be-detected image of the display panel including a special-shaped area;

[0112] In the specific implementation process, the researchers of this disclosure found that the area near the special-shaped area of the display panel after the glass cover plate is attached is the concentrated outbreak area of defects. The special-shaped area can be the bending area of a curved display panel, or a transparent non-display area opened in the display area of the display panel for accommodating electronic devices. This transparent display area can be a through-hole design for the display panel. In practical applications, for the area near the special-shaped area of the display panel, the image of the display panel including the special-shaped area can be collected by one or more image acquisition units. Correspondingly, the images from one or more image acquisition units can be obtained. It can be to collect the image of the display panel including the special-shaped area by one image acquisition unit. Correspondingly, the to-be-detected image can be one. It can also be to collect the image of the display panel including the special-shaped area by multiple image acquisition units. Correspondingly, the to-be-detected images can be multiple. In order to ensure the accuracy of the to-be-detected image obtained, and further ensure the accuracy of image detection, the image acquisition unit can be a high-precision Charge Coupled Device camera (CCD camera).

[0113] S102: Calculate the position coordinates of the ink area from the to-be-detected image;

[0114] In the specific implementation process, the ink located in the ink area can prevent light leakage at the edge of the display panel and ensure the display quality of the display panel.

[0115] S103: Determine the defect detection area in the image to be detected according to the coordinate position of the ink area;

[0116] In the specific implementation process, to determine the defect detection area in the image to be detected according to the coordinate position of the ink area, the area in the image to be detected except the coordinate position of the ink area can be used as the area for defect detection of the display panel. In this way, it is not necessary to perform defect detection on all areas in the image to be detected, and only the defect detection area except the coordinate position of the ink area in the image to be detected needs to be detected, improving the efficiency of defect detection.

[0117] S104: Determine the defective defects in the image to be detected by statistically analyzing the feature information of multiple pixel points in the defect detection area.

[0118] In the specific implementation process, to determine the defective defects in the image to be detected by statistically analyzing the feature information of multiple pixel points in the defect detection area, where the defective defects can be bubble defects, stain defects, etc. In this way, the defective defects can be directly detected from the defect detection area, thereby improving the efficiency of defect detection while realizing automatic defect detection.

[0119] In the embodiments of the present disclosure, as Figure 2 shown, step S102: Calculate the coordinate position of the ink area from the image to be detected, including:

[0120] S201: Perform binarization processing on the image to be detected according to the first threshold;

[0121] S202: Determine the coordinate position of the ink area according to the coordinates of the white pixel points in the image to be detected after binarization processing according to the first threshold.

[0122] In the specific implementation process, the specific implementation processes of steps S201 to S202 are as follows:

[0123] First, perform binarization processing on the image to be detected according to the first threshold, where the first threshold is a preset gray value. In this way, each pixel point at each coordinate position in the image to be detected after binarization processing is either a bright point or a dark point. Since the gray value of the pixel points located in the ink area is usually relatively large, the pixel points located in the ink area are white pixel points after binarization processing. In this way, the coordinate position of the ink area can be determined according to the coordinates of the white pixel points in the image to be detected after binarization processing according to the first threshold, thus realizing the rapid positioning of the coordinate position of the ink area. As Figure 3Shown is one of the schematic diagrams of the to-be-detected image after binarization processing. Among them, label C represents the ink area, and the ink area is a regular rectangle. In practical applications, the ink area can also be other shapes, which are not limited herein.

[0124] In the embodiment of the present disclosure, before step S102: calculating the position coordinates of the ink area from the to-be-detected image, the method further includes:

[0125] Performing compression processing, median filtering, and image deep copy processing on the to-be-detected image.

[0126] In the specific implementation process, before calculating the position coordinates of the ink area from the to-be-detected image, image preprocessing can be performed on the to-be-detected image first. The image preprocessing includes compression processing, median filtering, and image deep copy processing. Specifically, performing compression processing on the to-be-detected image, and the compression processing can be proportional compression processing. For example, it is proportionally reduced to one-sixteenth of the original, thereby improving the processing efficiency of defect detection. Further performing median filtering processing on the compressed image to further remove the noise in the image and improve the efficiency and accuracy of defect detection. Performing image deep copy processing on the to-be-detected image. In this way, parts of the image after the deep copy processing can be marked according to actual needs, further ensuring the efficiency of defect detection.

[0127] In the embodiment of the present disclosure, as Figure 4 shown, step S202: determining the coordinate position of the ink area according to the coordinates of the white pixel points in the to-be-detected image after binarization processing according to the first threshold includes:

[0128] S301: In the image coordinate system, obtaining the ordinate range of the ink area from the to-be-detected image after binarization processing according to the first threshold, where the ordinate range includes a starting ordinate and an ending ordinate;

[0129] S302: Calculating a first abscissa array of the ink area at the starting ordinate, a second abscissa array at the ending ordinate, and a third abscissa array at a preset coordinate position between the starting ordinate and the ending ordinate;

[0130] S303: Determining the first abscissa-ordinate range where the ink area is located according to the starting ordinate, the first abscissa array, the ending ordinate, the second abscissa array, the preset coordinate position, and the third abscissa array;

[0131] S304: Using the first abscissa-ordinate range as the coordinate position of the ink area in the image coordinate system.

[0132] In the specific implementation process, the specific implementation process of step S301 to step S304 is as follows:

[0133] First, in the image coordinate system, the coordinates of the white pixels are determined from the image to be detected after the first threshold value binarization process, wherein the first dimension of the coordinates of the white pixels is the ordinate and the second dimension is the abscissa, that is, the abscissa and ordinate of all the white pixels in the image to be detected are determined. Then, the coordinate position of the ink area is determined according to the coordinates of the white pixels. Specifically, in the image coordinate system, the ordinate range of the ink area is obtained from the image to be detected after the first threshold value binarization process, wherein the ordinate range includes a starting ordinate and an ending ordinate, and may be the ordinate range of the ink area away from the side of the irregular area. After determining the ordinate range, the ordinate corresponding to the ordinate range may be determined, and then the ordinate at the preset coordinate position of the ordinate may be determined, and the abscissa of all the white pixels corresponding to the ordinate at the preset coordinate position may be further determined, wherein the number of pixels corresponding to the abscissa of all the white pixels corresponding to the ordinate at the preset coordinate position may be greater than 5. Then, the minimum horizontal coordinate, the middle horizontal coordinate and the maximum horizontal coordinate in the values of the horizontal coordinates of all the white pixel points corresponding to the vertical coordinate at the preset coordinate position are determined, and then, the third horizontal coordinate array at the preset coordinate position is determined according to the minimum horizontal coordinate, the middle horizontal coordinate and the maximum horizontal coordinate, and then, the starting vertical coordinate of the ink area and the first horizontal coordinate array at the starting vertical coordinate, as well as the second horizontal coordinate array at the ending vertical coordinate and the second horizontal coordinate array at the ending vertical coordinate are determined according to the third horizontal coordinate array, and then the first horizontal and vertical coordinate range of the ink area is determined, and then, the first horizontal and vertical coordinate range is used as the coordinate position of the ink area in the image coordinate system, thereby realizing the positioning of the ink area in the image to be detected.

[0134] Still Figure 3 Taking the image to be detected as an example, the ink area C is away from the side of the irregular area. Figure 5As shown by the dashed line aa' in [description], the vertical coordinate range can be [y0, y], the starting vertical coordinate can be y0, and the ending vertical coordinate can be y. Then, calculate the first abscissa array of the ink area at the starting vertical coordinate, the second abscissa array of the ink area at the ending vertical coordinate. The first abscissa array can represent the abscissa range of the ink area at the starting vertical coordinate, and the second abscissa array can represent the abscissa range of the ink area at the ending vertical coordinate. In addition, calculate the third abscissa array at a preset coordinate position between the starting vertical coordinate and the ending vertical coordinate. The third abscissa array can represent the abscissa range of the ink area at the preset coordinate position within the vertical coordinate range. In a specific implementation process, the preset coordinate position can be the position at one-third of the vertical coordinate range, such as Figure 5 as described in [reference], the preset coordinate position (indicated by label Y) is the position at one-third of the vertical coordinate range, and it can also be the position at one-half of the vertical coordinate range. Those skilled in the art can select the preset coordinate position according to actual application needs, and no limitation is made here. Then, according to the starting vertical coordinate, the first abscissa array, the ending vertical coordinate, the second abscissa array, the preset coordinate position, and the third abscissa array, determine the first horizontal and vertical coordinate range where the ink area is located, and use the first horizontal and vertical coordinate range as the coordinate position of the ink area in the image coordinate system, thereby realizing the positioning of the ink area in the image coordinate system.

[0135] In the embodiments of the present disclosure, as Figure 6 shown, after step S102: calculating the position coordinates of the ink area from the image to be detected, the method further includes:

[0136] S401: Binarize the image to be detected according to a second threshold;

[0137] S402: Determine the position coordinates of the reflective area according to the coordinates of the white pixel points in the image to be detected after binarization according to the second threshold and the coordinate position of the ink area;

[0138] Correspondingly, step S103: determining the defect detection area in the image to be detected according to the coordinate position of the ink area includes:

[0139] Determine the defect detection area in the image to be detected according to the coordinate position of the ink area and the position coordinates of the reflective area.

[0140] In a specific implementation process, the specific implementation processes of steps S401 to S402 are as follows:

[0141] After calculating the position coordinates of the ink area from the image to be detected, the image to be detected is binarized according to the second threshold, where the second threshold is a preset gray value, and the second threshold and the first threshold may be the same gray value or different gray values, which is not limited herein. After binarization according to the second threshold, each pixel point in the image to be detected is either a bright point or a dark point. In practical applications, the researchers of the present disclosure found that the stage for carrying the display panel is usually made of a metal material, and during the process of the image acquisition unit acquiring the image to be detected, there are often large-area reflective regions in the image to be detected. Specifically, the position coordinates of the reflective region are determined according to the coordinates of the white pixel points and the ink area coordinate position in the image to be detected after binarization according to the second threshold. After determining the position coordinates of the reflective region, the defect detection region in the image to be detected is determined according to the ink area coordinate position and the position coordinates of the reflective region. In this way, before defect detection of the display panel, the interference of the ink area and the reflective region on defect detection can be excluded first, and then the defect detection region in the image to be detected is determined, thereby improving the efficiency of defect detection.

[0142] In the embodiment of the present disclosure, as Figure 7 shown, step S402: determining the position coordinates of the reflective region according to the coordinates of the white pixel points and the ink area coordinate position in the image to be detected after binarization according to the second threshold, includes:

[0143] S501: calculating, from the coordinates of the white pixel points in the image to be detected after binarization according to the second threshold excluding the ink area coordinate position, a plurality of pixel points that are located in the same connected domain and simultaneously satisfy that the ordinate is less than the starting ordinate and greater than the first preset number;

[0144] S502: determining the second horizontal and vertical coordinate ranges of the connected domain in the image coordinate system;

[0145] S503: taking the second horizontal and vertical coordinate ranges as the coordinate position of the reflective region in the image coordinate system.

[0146] In the specific implementation process, the specific implementation processes of steps S501 to S503 are as follows:

[0147] First, except for the coordinate positions of the ink regions, from the coordinates of the white pixel points in the to-be-detected image after binarization processing according to the second threshold, calculate multiple pixel points that are located in the same connected domain and simultaneously satisfy that the ordinate is less than the starting ordinate and greater than a first preset number. The first preset number can be a number set by those skilled in the art according to actual application needs. For example, the first preset number is 400. Among them, the multiple pixel points are bright points with a gray value greater than a preset value. Then, determine the second horizontal and vertical coordinate ranges of the connected domain in the image coordinate system, and use the second horizontal and vertical coordinate ranges as the coordinate positions of the reflective region in the image coordinate system. The coordinate positions of the reflective region in the to-be-detected image can be, for example, Figure 5 the position shown by label D in

[0148] In the embodiment of the present disclosure, as Figure 8 shown, step S104: Determine the defective defects in the to-be-detected image by statistically analyzing the feature information of multiple pixel points in the defect detection region, including:

[0149] S601: Re-acquire the to-be-detected image, and sequentially perform grayscale processing, median filtering processing, same-scale reduction processing, and binarization processing according to a third threshold on the to-be-detected image;

[0150] S602: Determine the defective defects in the to-be-detected image by statistically analyzing the feature information of multiple pixel points in the defect detection region after binarization processing according to the third threshold.

[0151] In the specific implementation process, the specific implementation processes of steps S601 to S602 are as follows:

[0152] After determining the defect detection area in the image to be detected according to the coordinate position of the ink area, the image to be detected is acquired again, and the image to be detected is grayscale processed to obtain a grayscale processed image. For example, the image to be detected can be reread in grayscale mode, and then the grayscale processed image is median filtered to obtain a filtered image. Then, the filtered image is scaled down proportionally to obtain a scaled-down image. Then, the scaled-down image is binarized according to a third threshold to obtain a black-and-white image, where the third threshold is a preset grayscale value. The defective defects in the image to be detected are determined by statistically analyzing the feature information of multiple pixel points in the defect detection area after binarization according to the third threshold. In a specific implementation process, re-acquiring the image to be detected for defective defect detection avoids the lack of details and improves the detection accuracy. In addition, sequentially performing grayscale processing, median filtering, and proportional scaling on the image to be detected improves the defect detection efficiency, and binarization according to the third threshold realizes the detection of defective defects.

[0153] In the embodiments of the present disclosure, as Figure 9 shown, step S602: determining the defective defects in the image to be detected by statistically analyzing the feature information of multiple pixel points in the defect detection area after binarization according to the third threshold includes:

[0154] S701: statistically analyzing at least one set of pixel points from multiple pixel points in the defect detection area after binarization according to the third threshold, where the pixel points in the set of pixel points have the same grayscale value and are located in the same connected component;

[0155] S702: calculating the number of pixel points in each set of pixel points;

[0156] S703: taking the connected component where the set of pixel points with the number of pixel points greater than a second preset number is located as the defective defect area in the image to be detected.

[0157] In a specific implementation process, the specific implementation process of steps S701 to S703 is as follows:

[0158] First, at least one set of pixel points is counted from multiple pixel points within the defect detection region after binarization according to the third threshold. The pixel points in the set of pixel points have the same grayscale value and are located in the same connected component. Each pixel point in the set of pixel points is a bright point. Among them, the specific determination process of the connected component is as follows: the coordinate positions of each white pixel point are determined from the defect detection region after binarization according to the third threshold. If the distance between the coordinate positions of two adjacent white pixel points is less than a preset distance threshold, and the preset distance threshold is a value set according to actual application needs, it indicates that the two adjacent white pixel points are located in the same connected component, where the grayscale value of each white pixel point is the same grayscale value. Then, the number of pixel points in each set of pixel points is calculated, and the connected component where the set of pixel points with the number of pixel points greater than the second preset number is located is used as the defective area in the image to be detected. Among them, the second preset number is a preset number. For example, the second preset number is 200. For example, the connected component where the set of pixel points with the number of pixel points greater than the second preset number is located can be the area shown by label E in Figure 5 as shown in the figure, in this way, the detection of defective areas within the defect detection region is realized, and it is not necessary to detect all areas within the region to be detected, improving the efficiency of defect detection.

[0159] In the embodiment of the present disclosure, after step S703: using the connected component where the set of pixel points with the number of pixel points greater than the second preset number is located as the defective area in the image to be detected, the method further includes:

[0160] Mark the connected component where the set of pixel points is located to prompt that there is a defect at the corresponding position of the display panel and the defective area in the image to be detected.

[0161] In the specific implementation process, after using the connected component where the set of pixel points with the number of pixel points greater than the second preset number is located as the defective area in the image to be detected, mark the connected component where the set of pixel points is located. For example, use the OPEN CV computer vision library to draw a circle to mark the defective area. The drawn circle can be circular or elliptical, which is not limited here. In this way, the user can be prompted that there is a defect at the corresponding position of the display panel and the defective area in the image to be detected, such as a bubble. In addition, in the specific implementation process, other methods other than drawing a circle can also be used to mark the defective area, which is not limited here. In addition, the marked result can be written into the corresponding picture file of the image to be detected so that the user can view it at any time, thereby improving the user experience.

[0162] In the embodiments of the present disclosure, as Figure 10 shown, before step S201: performing binarization processing on the image to be detected according to a first threshold, the method further includes:

[0163] S801: performing a proportional reduction process on the image to be detected to obtain a reduced image;

[0164] S802: performing median filtering on the reduced image to obtain a filtered image, and using the filtered image as the image to be detected.

[0165] In a specific implementation process, the specific implementation processes of steps S801 to S802 are as follows:

[0166] Before performing binarization processing on the image to be detected according to the first threshold, the image to be detected can be first proportionally reduced, for example, reduced to one-sixteenth of the original, to obtain a reduced image, thereby improving the efficiency of defect detection. Optionally, the reduced image can be further subjected to median filtering to obtain a filtered image, thereby removing the noise in the image to be detected. Then, the reduced image is used as the image to be detected. That is to say, before performing binarization processing on the image to be detected, preprocessing such as proportional reduction and median filtering can be sequentially performed on the image to be detected, thereby improving the defect detection rate of the subsequent image to be detected.

[0167] Based on the same inventive concept, as Figure 11 shown, the embodiments of the present disclosure provide a detection device for a display panel, which includes:

[0168] An acquisition unit 10, configured to acquire an image to be detected including a special-shaped area of the display panel;

[0169] A calculation unit 20, configured to calculate the position coordinates of the ink area from the image to be detected;

[0170] A first determination unit 30, configured to determine a defect detection area in the image to be detected according to the coordinate position of the ink area;

[0171] A second determination unit 40, configured to determine a defective defect in the image to be detected by statistically analyzing the feature information of a plurality of pixel points in the defect detection area.

[0172] Optionally, in the embodiments of the present disclosure, the calculation unit 20 is configured to:

[0173] perform binarization processing on the image to be detected according to a first threshold;

[0174] Determine the coordinate position of the ink area according to the coordinates of the white pixel points in the image to be detected after binarization processing according to the first threshold.

[0175] Optionally, in an embodiment of the present disclosure, before the calculation unit 20 calculates the position coordinates of the ink area from the image to be detected, the device further includes a preprocessing unit, and the preprocessing unit is configured to:

[0176] Perform compression processing, median filtering, and image deep copy processing on the image to be detected.

[0177] Optionally, in an embodiment of the present disclosure, the calculation unit 20 is configured to:

[0178] In the image coordinate system, obtain the ordinate range of the ink area from the image to be detected after binarization processing according to the first threshold, where the ordinate range includes a starting ordinate and an ending ordinate;

[0179] Calculate a first abscissa array at the starting ordinate of the ink area, a second abscissa array at the ending ordinate, and a third abscissa array at a preset coordinate position between the starting ordinate and the ending ordinate;

[0180] Determine a first abscissa-ordinate range where the ink area is located according to the starting ordinate, the first abscissa array, the ending ordinate, the second abscissa array, the preset coordinate position, and the third abscissa array;

[0181] Use the first abscissa-ordinate range as the coordinate position of the ink area in the image coordinate system.

[0182] Optionally, in an embodiment of the present disclosure, after the calculation unit 20 calculates the position coordinates of the ink area from the image to be detected, the calculation unit 20 is further configured to: perform binarization processing on the image to be detected according to a second threshold;

[0183] Determine the position coordinates of the reflective area according to the coordinates of the white pixel points in the image to be detected after binarization processing according to the second threshold and the coordinate position of the ink area;

[0184] The first determination unit 30 is configured to: determine a defect detection area in the image to be detected according to the coordinate position of the ink area and the position coordinates of the reflective area; the calculation unit 20 is configured to:

[0185] Excluding the coordinate position of the ink area from the coordinates of the white pixel points in the image to be detected after binarization processing according to the second threshold, calculate a plurality of pixel points that are located in the same connected domain and simultaneously satisfy that the ordinate is less than the starting ordinate and greater than a first preset number;

[0186] Determine the second horizontal and vertical coordinate ranges of the connected domain in the image coordinate system;

[0187] Use the second horizontal and vertical coordinate ranges as the coordinate positions of the reflective area in the image coordinate system.

[0188] Optionally, in the embodiments of the present disclosure, the second determination unit 40 is configured to:

[0189] Re-obtain the image to be detected, and sequentially perform grayscale processing, median filtering processing, same-scale reduction processing, and binarization processing according to a third threshold on the image to be detected;

[0190] Determine the defective defects in the image to be detected by statistically analyzing the feature information of multiple pixel points in the defect detection area after binarization processing according to the third threshold.

[0191] Optionally, in the embodiments of the present disclosure, the second determination unit 40 is configured to:

[0192] Statistically obtain at least one set of pixel points from the multiple pixel points in the defect detection area after binarization processing according to the third threshold, and the pixel points in the set of pixel points are located in the same connected domain;

[0193] Calculate the number of pixel points in each set of pixel points;

[0194] Use the connected domain where the set of pixel points with the number of pixel points greater than the second preset number is located as the defective defect area in the image to be detected.

[0195] Optionally, in the embodiments of the present disclosure, the device further includes a marking unit, and the marking unit is configured to:

[0196] Mark the connected domain where the set of pixel points is located to indicate that there are defective defects at the corresponding positions of the display panel and the defective defect area in the image to be detected.

[0197] Optionally, in the embodiments of the present disclosure, the device further includes an image processing unit, and the image processing unit is configured to:

[0198] Perform same-scale reduction processing on the image to be detected to obtain a reduced image;

[0199] Perform median filtering processing on the reduced image to obtain a filtered image, and use the filtered image as the image to be detected.

[0200] Based on the same inventive concept, as Figure 12 shown, the embodiments of the present disclosure further provide a detection system for a display panel, which includes:

[0201] A stage 100, configured to place the display panel 200;

[0202] An image acquisition unit 300, configured to acquire a to-be-detected image of the display panel 200 including the special-shaped area 201;

[0203] An industrial personal computer 400, configured to obtain the to-be-detected image of the display panel 200 including the special-shaped area 201 from the image acquisition unit 300; calculate the position coordinates of the ink area from the to-be-detected image; determine the defect detection area in the to-be-detected image according to the coordinate position of the ink area; and determine the defective defects in the to-be-detected image by statistically analyzing the feature information of a plurality of pixel points in the defect detection area.

[0204] In a specific implementation process, the display panel 100 may be a curved display panel or a flat display panel. For example, Figure 12 As shown, the display panel 100 is a curved display panel. Correspondingly, the special-shaped area 201 is a schematic structural diagram of one of the bending areas.

[0205] In an embodiment of the present disclosure, the image acquisition unit 300 may be one or more, and each image acquisition unit 300 is a line-scan camera. In a specific implementation process, in addition to including a corresponding line-scan camera, each image acquisition unit 300 is also equipped with a point light source. The point light source L is used to illuminate the display panel 200, and the point light sources do not interfere with each other. When using multiple image acquisition units 300 to acquire the to-be-detected image and perform defect detection such as bubbles, if there are defective defects in the to-be-detected image acquired by any one of the image acquisition units 300, it is determined that the display panel has defective defects, thereby ensuring the accuracy of defect detection. For example, Figure 13 As shown, when the image acquisition unit 300 is three, it specifically includes a line-scan camera S1 and a point light source L1, a line-scan camera S2 and a point light source L2, and a line-scan camera S3 and a point light source L3, which is a schematic structural diagram of image acquisition of the display panel 200. Of course, those skilled in the art can set the image acquisition unit 300 according to actual application needs, and no limitation is made here.

[0206] Based on the same inventive concept, as Figure 14 shown, an embodiment of the present disclosure further provides a detection device for a display panel, which includes:

[0207] A memory 1 and a processor 2;

[0208] Wherein, the memory 1 is used to store a computer program;

[0209] The processor 2 is used to execute the computer program in the memory 1 to implement the following steps:

[0210] Obtain a to-be-detected image of the display panel including a special-shaped area;

[0211] Calculate the position coordinates of the ink area from the to-be-detected image;

[0212] Determine the defect detection area in the to-be-detected image according to the coordinate position of the ink area;

[0213] Determine the defective defects in the to-be-detected image by statistically analyzing the feature information of multiple pixel points in the defect detection area.

[0214] Based on the same inventive concept, an embodiment of the present disclosure also provides a computer non-transitory readable storage medium, wherein:

[0215] The storage medium stores computer instructions, and when the computer instructions run on a computer, the computer is caused to execute the detection method of the display panel as described above.

[0216] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memories, CD-ROMs, optical memories, etc.) containing computer-usable program codes.

[0217] The present application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram can be implemented by computer program instructions, and the combination of the flows and / or blocks in the flowchart and / or block diagram can also be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in Figure 1 one or more flows and / or blocks Figure 1 one or more blocks.

[0218] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including an instruction device, and the instruction device implements the functions in Figure 1 one or more flows and / or blocksFigure 1 The functions specified in one or more boxes.

[0219] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process. Thus, the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more processes and / or boxes Figure 1 One process or more processes and / or boxes Figure 1 The steps of the functions specified in one or more boxes.

[0220] Although the preferred embodiments of the present disclosure have been described, those skilled in the art can make additional changes and modifications once they learn the basic creative concepts. Therefore, the appended claims are intended to be construed to include the preferred embodiments as well as all changes and modifications falling within the scope of the present disclosure.

[0221] Obviously, those skilled in the art can make various changes and modifications to the present disclosure without departing from the spirit and scope of the present disclosure. Thus, if these modifications and variations of the present disclosure fall within the scope of the claims of the present disclosure and their equivalent technologies, the present disclosure also intends to include these modifications and variations.

Claims

1. A detection method for a display panel, wherein, Including: Obtaining a to-be-detected image of the display panel including a special-shaped area; wherein, when the display panel is a curved display panel, the special-shaped area is the bending area of the curved display panel; or, the special-shaped area is a transparent non-display area opened in the display area of the display panel for accommodating electronic devices; Calculating the position coordinates of the ink area from the to-be-detected image; Determining a defect detection area in the to-be-detected image according to the coordinate position of the ink area; wherein, the area in the to-be-detected image other than the coordinate position of the ink area is the area for defect detection of the display panel; Determining a defective defect in the to-be-detected image by statistically analyzing the feature information of multiple pixel points in the defect detection area.

2. The method according to claim 1, wherein, The calculating the position coordinates of the ink area from the to-be-detected image includes: Performing binarization processing on the to-be-detected image according to a first threshold; Determining the coordinate position of the ink area according to the coordinates of the white pixel points in the to-be-detected image after binarization processing according to the first threshold.

3. The method according to claim 1, wherein, Before calculating the position coordinates of the ink area from the to-be-detected image, the method further includes: Performing compression processing, median filtering, and image deep copy processing on the to-be-detected image.

4. The method according to claim 2, wherein The determining the coordinate position of the ink area according to the coordinates of the white pixel points in the to-be-detected image after binarization processing according to the first threshold includes: In the image coordinate system, obtaining the ordinate range of the ink area from the to-be-detected image after binarization processing according to the first threshold, where the ordinate range includes a starting ordinate and an ending ordinate; Calculating a first abscissa array of the ink area at the starting ordinate, a second abscissa array of the ink area at the ending ordinate, and a third abscissa array at a preset coordinate position between the starting ordinate and the ending ordinate; Determining a first abscissa-ordinate range where the ink area is located according to the starting ordinate, the first abscissa array, the ending ordinate, the second abscissa array, the preset coordinate position, and the third abscissa array; Taking the first abscissa-ordinate range as the coordinate position of the ink area in the image coordinate system.

5. The method according to claim 4, wherein After calculating the position coordinates of the ink area from the to-be-detected image, the method further includes: Performing binarization processing on the to-be-detected image according to a second threshold; Determining the position coordinates of the reflective area according to the coordinates of the white pixel points in the to-be-detected image after binarization processing according to the second threshold and the coordinate position of the ink area; The determining the defect detection area in the to-be-detected image according to the coordinate position of the ink area includes: Determining the defect detection area in the to-be-detected image according to the coordinate position of the ink area and the position coordinates of the reflective area.

6. The method according to claim 5, wherein, The determining the position coordinates of the reflective area according to the coordinates of the white pixel points in the to-be-detected image after binarization processing according to the second threshold and the coordinate position of the ink area includes: From the coordinates of the white pixel points in the to-be-detected image after binarization according to the second threshold, excluding the coordinate positions of the ink areas, calculate a plurality of pixel points that are located in the same connected domain and simultaneously satisfy that the ordinate is less than the starting ordinate and greater than the first preset number; Determine the second horizontal and vertical coordinate ranges of the connected domain in the image coordinate system; Use the second horizontal and vertical coordinate ranges as the coordinate positions of the reflective area in the image coordinate system.

7. The method according to any one of claims 1 to 6, wherein, The determining the defective defects in the to-be-detected image by statistically analyzing the feature information of a plurality of pixel points in the defect detection area includes: Re-acquire the to-be-detected image, and sequentially perform graying processing, median filtering processing, same-scale reduction processing, and binarization processing according to a third threshold on the to-be-detected image; Determine the defective defects in the to-be-detected image by statistically analyzing the feature information of a plurality of pixel points in the defect detection area after binarization processing according to the third threshold.

8. The method according to claim 7, wherein, The determining the defective defects in the to-be-detected image by statistically analyzing the feature information of a plurality of pixel points in the defect detection area after binarization processing according to a third threshold includes: Statistically analyze at least one set of pixel points from the plurality of pixel points in the defect detection area after binarization processing according to the third threshold, where the pixel points in the set of pixel points have the same gray value and are located in the same connected domain; Calculate the number of pixel points in each set of pixel points; Use the connected domain where the set of pixel points with the number of pixel points greater than the second preset number is located as the defective defect area in the to-be-detected image.

9. The method according to claim 8, wherein After using the connected domain where the set of pixel points with the number of pixel points greater than the second preset number is located as the defective defect area in the to-be-detected image, the method further includes: Mark the connected domain where the set of pixel points is located to prompt that there are defective defects at the corresponding position of the display panel and the defective defect area in the to-be-detected image.

10. The method according to claim 2, wherein, Before binarizing the to-be-detected image according to the first threshold, the method further includes: Perform same-scale reduction processing on the to-be-detected image to obtain a reduced image; Perform median filtering processing on the reduced image to obtain a filtered image, and use the filtered image as the to-be-detected image.

11. A detecting device for a display panel, wherein, Includes: An acquisition unit for acquiring a to-be-detected image of the display panel including a special-shaped area; wherein, when the display panel is a curved display panel, the special-shaped area is the bent area of the curved display panel; or, the special-shaped area is a transparent non-display area opened in the display area of the display panel for accommodating electronic devices; A calculation unit for calculating the coordinate positions of the ink areas from the to-be-detected image; A first determination unit for determining the defect detection area in the to-be-detected image according to the coordinate positions of the ink areas; wherein, the area in the to-be-detected image except the coordinate positions of the ink areas is the area for defect detection of the display panel; A second determination unit for determining the defective defects in the to-be-detected image by statistically analyzing the feature information of a plurality of pixel points in the defect detection area.

12. The apparatus according to claim 11, wherein, The calculation unit is configured to: Binarize the image to be detected according to a first threshold; Determine the coordinate position of the ink area based on the coordinates of the white pixel points in the image to be detected after binarization according to the first threshold.

13. The apparatus according to claim 12, wherein, The calculation unit is configured to: In the image coordinate system, obtain the vertical coordinate range of the ink area from the image to be detected after binarization according to the first threshold, where the vertical coordinate range includes a starting vertical coordinate and an ending vertical coordinate; Calculate a first abscissa array at the starting vertical coordinate of the ink area, a second abscissa array at the ending vertical coordinate, and a third abscissa array at a preset coordinate position between the starting vertical coordinate and the ending vertical coordinate; Determine the first horizontal and vertical coordinate range where the ink area is located based on the starting vertical coordinate, the first abscissa array, the ending vertical coordinate, the second abscissa array, the preset coordinate position, and the third abscissa array; Use the first horizontal and vertical coordinate range as the coordinate position of the ink area in the image coordinate system.

14. The apparatus according to claim 13, wherein, After the calculation unit calculates the position coordinates of the ink area from the image to be detected, the calculation unit is further configured to: Binarize the image to be detected according to a second threshold; Determine the position coordinates of the reflective area based on the coordinates of the white pixel points in the image to be detected after binarization according to the second threshold and the ink area coordinate position; The first determination unit is configured to: determine the defect detection area in the image to be detected based on the ink area coordinate position and the position coordinates of the reflective area; The calculation unit is configured to: calculate, from the coordinates of the white pixel points in the image to be detected after binarization according to the second threshold excluding the ink area coordinate position, multiple pixel points that are located in the same connected domain and simultaneously satisfy that the vertical coordinate is less than the starting vertical coordinate and greater than a first preset number; Determine the second horizontal and vertical coordinate range of the connected domain in the image coordinate system; Use the second horizontal and vertical coordinate range as the coordinate position of the reflective area in the image coordinate system.

15. The device according to any one of claims 11-14, wherein, The second determination unit is configured to: Re-acquire the image to be detected, and sequentially perform grayscale processing, median filtering processing, same-scale reduction processing, and binarization processing according to a third threshold on the image to be detected; Determine the defective defects in the image to be detected by statistically analyzing the characteristic information of multiple pixel points in the defect detection area after binarization according to the third threshold.

16. The device according to claim 15, wherein, The device further includes a marking unit, and the marking unit is configured to: Mark the connected domain where the pixel point set is located to prompt that there are defective defects at the corresponding position of the display panel and the defective defect area in the image to be detected.

17. A detection system for a display panel, wherein, Comprising: A stage configured to place the display panel; An image acquisition unit configured to acquire the image to be detected of the display panel including the special-shaped area; wherein, when the display panel is a curved display panel, the special-shaped area is the bending area of the curved display panel; or, the special-shaped area is a transparent non-display area opened in the display area of the display panel for accommodating electronic devices. An industrial control computer is configured to obtain a to-be-detected image of the display panel including a special-shaped area from the image acquisition unit; calculate the position coordinates of the ink area from the to-be-detected image; determine a defect detection area in the to-be-detected image according to the coordinate position of the ink area; determine a defective defect in the to-be-detected image by statistically analyzing the feature information of a plurality of pixel points in the defect detection area; wherein, the area in the to-be-detected image other than the coordinate position of the ink area is the area for defect detection of the display panel.

18. The system according to claim 17, wherein, The image acquisition unit can be one or more, and each image acquisition unit is a line scan camera.

19. A detecting device for a display panel, wherein, Comprising: A memory and a processor; Wherein, the memory is used to store computer programs; The processor is used to execute the computer programs in the memory to implement the following steps: Obtain a to-be-detected image of the display panel including a special-shaped area; wherein, when the display panel is a curved display panel, the special-shaped area is the bending area of the curved display panel; or, the special-shaped area is a transparent non-display area opened in the display area of the display panel for accommodating electronic devices; Calculate the position coordinates of the ink area from the to-be-detected image; Determine a defect detection area in the to-be-detected image according to the coordinate position of the ink area; wherein, the area in the to-be-detected image other than the coordinate position of the ink area is the area for defect detection of the display panel; Determine a defective defect in the to-be-detected image by statistically analyzing the feature information of a plurality of pixel points in the defect detection area.

20. A computer non-transitory readable storage medium, wherein: The storage medium stores computer instructions, and when the computer instructions run on a computer, the computer is caused to execute the detection method of the display panel according to any one of claims 1-10.

Images