Liquid crystal display panel defect detection method, device and electronic equipment

Abstract

The application provides a liquid crystal display panel defect detection method and device and electronic equipment, and relates to the technical field of liquid crystal display panel detection. The method comprises the following steps: acquiring images of a plurality of target layers of a liquid crystal display panel captured by a camera, wherein the plurality of target layers comprise an upper surface layer and a plurality of structure layers of the liquid crystal display panel; extracting a defect area of each target layer corresponding image to obtain a defect area corresponding to each target layer; measuring the saliency of the defect area of each target layer by energy gradient, and then determining the target layer corresponding to the maximum saliency in the determined saliency as the layer where the defect is located. The technical scheme provided by the application can improve the accuracy of liquid crystal display panel defect detection.

Description

Technical Field

[0001] This application relates to the field of liquid crystal display panel defect detection technology, and in particular to a method, apparatus and equipment for detecting defects in liquid crystal display panels. Background Technology

[0002] Thanks to the perfect combination of semiconductor technology, liquid crystal material technology, and active light emission technology, LCD monitors have rapidly become the mainstream in the current display market, and the quality of the LCD panel is related to the overall performance of the LCD monitor.

[0003] During the manufacturing process, LCD panels may contain defects, such as structural defects in the internal layers or foreign matter defects caused by dust or other contaminants entering during the bonding process. These internal defects can lead to the production of substandard products. To ensure product quality, defect detection of LCD panels is necessary.

[0004] Besides internal defects in the LCD panel, dust and dirt may adhere to the panel surface. These deposits do not affect the quality of the panel, but their presence can easily be identified as internal defects by existing testing methods, reducing the accuracy of defect detection results. Summary of the Invention

[0005] In view of this, embodiments of this application provide a method, apparatus, and electronic device for detecting defects in a liquid crystal display panel, which can improve the accuracy of panel defect detection results.

[0006] To achieve the above objectives, in a first aspect, embodiments of this application provide a method for detecting defects in a liquid crystal display panel, comprising:

[0007] The camera captures images of multiple target layers of the liquid crystal display panel, including the upper surface layer and multiple structural layers of the liquid crystal display panel.

[0008] Defect regions are extracted from the image corresponding to each target layer to obtain the defect regions corresponding to each target layer.

[0009] The salience of the defect region in each target layer is measured by the energy gradient, and then the target layer with the highest salience is determined as the layer where the defect is located.

[0010] The liquid crystal display panel defect detection method provided in this embodiment allows the electronic device to acquire images of the upper surface layer and internal structural layer of the panel captured by a camera during panel defect detection. The defect area is extracted from the image, and the layer where the defect is located is determined. This distinguishes whether the defect is located on the panel surface or inside the panel, thereby improving the accuracy of defect detection and more accurately locating the layer where the defect is located.

[0011] In one possible implementation of the first aspect, images are acquired by a camera targeting multiple target layers of a liquid crystal display panel, the multiple target layers including an upper surface layer of the liquid crystal display panel and multiple structural layers, including:

[0012] The camera captures an image of the upper surface layer of the liquid crystal display panel at a first imaging position. At the first imaging position, the camera's focus point is located on the upper surface layer, and the quality of the captured image meets the target requirements.

[0013] Based on the physical distance between adjacent layers in each target layer, the camera is controlled to move sequentially towards each structural layer, acquiring images captured when the camera's focal point moves to each structural layer.

[0014] Through the above implementation method, not only can images of multiple target layers of the liquid crystal display panel be acquired, but the imaging effect of the images captured by the camera can also be improved, providing images that meet the target requirements for subsequent image processing, thereby improving the efficiency of defect detection and the accuracy of detection results.

[0015] In one possible implementation of the first aspect, the first imaging position is determined based on a predetermined optimal imaging distance between the camera and the upper surface layer of the liquid crystal display panel.

[0016] The above implementation methods can improve the efficiency of image acquisition and the imaging effect, reduce the difficulty of subsequent defect identification and extraction, and thus improve the accuracy of detection results.

[0017] In one possible implementation of the first aspect, the relative distance between the camera and the liquid crystal display panel can be determined by a distance sensor.

[0018] Through the above implementation process, the distance between the camera and the LCD panel can be accurately obtained, reducing distance errors during the detection process and thus improving the accuracy of the detection results.

[0019] In one possible implementation of the first aspect, the method for determining the optimal imaging distance may include:

[0020] By moving the camera above the LCD panel at a preset distance, multiple images of the panel's upper surface layer are captured at different distances from the panel.

[0021] Among the multiple images of the upper surface layer acquired, the image with the best imaging effect is determined, the camera position corresponding to the image with the best imaging effect is obtained, the distance of the camera relative to the upper surface of the panel is recorded, and this distance is determined as the optimal imaging distance.

[0022] The above implementation process can improve the imaging effect of the captured images, thereby improving the accuracy of the detection results.

[0023] In one possible implementation of the first aspect, defect region extraction is performed on the image corresponding to each target layer to obtain the defect region corresponding to each target layer, including:

[0024] For each target layer, image enhancement is performed on the image to obtain the enhanced image;

[0025] Defect regions are extracted from the enhanced image to obtain the first defect region;

[0026] The interference regions in the first defect region are filtered out to obtain the defect region corresponding to the target layer.

[0027] In the above embodiments, by performing image enhancement before determining the target layer where the defect is located, the defect information in the image can be enhanced, which facilitates the subsequent acquisition of the first defect region. By filtering out the interference region in the defect region, the main body of the defect can be obtained more accurately, thereby improving the accuracy of the detection results.

[0028] In one possible implementation of the first aspect, determining the target layer where the defect is located based on the salience of the defect region in the image corresponding to each target layer includes:

[0029] For each target layer from which defect regions are extracted, the ratio of the energy gradient of the defect region corresponding to the target layer to the energy gradient of the image corresponding to the target layer is determined; wherein, the ratio corresponding to each target layer is used to indicate the salience of the defect region in the image corresponding to the target layer;

[0030] The target layer corresponding to the largest ratio among the determined ratios is identified as the layer where the defect is located.

[0031] The above implementation method can conveniently and accurately determine the layer where the defect is located.

[0032] In one possible implementation of the first aspect, the method further includes: if it is determined that the defect is located in the liquid crystal layer, then determining whether the defect is a missing LED based on the image of the liquid crystal layer;

[0033] If it is determined that the defect is located in another structural layer outside the liquid crystal layer, then the size of the defect is determined.

[0034] The above-described methods can detect the cause and size of defects in the liquid crystal layer, which helps staff perform subsequent operations and effectively improves panel quality.

[0035] In one possible implementation of the first aspect, the method further includes:

[0036] Channel separation is performed on the image of the liquid crystal layer to obtain multiple single-channel images;

[0037] For each single-channel image, the defect region is extracted to obtain the corresponding defect region for each single-channel image;

[0038] Based on the area of ​​the defect region corresponding to each single-channel image, determine whether the defect is a missing LED bead.

[0039] The above-described implementation method can more accurately detect specific defects in the liquid crystal layer.

[0040] Secondly, embodiments of this application provide a liquid crystal display panel defect detection device, which includes: a control module, an acquisition module, an extraction module, and a determination module, wherein:

[0041] The control module is used to control the camera to move according to the physical distance between adjacent layers in each structural layer, so that the camera's focus point is successively located on the upper surface layer and each structural layer, and to capture images of the upper surface layer and each structural layer.

[0042] An acquisition module is used to acquire images captured by a camera targeting multiple target layers of a liquid crystal display panel, wherein the multiple target layers include the upper surface layer of the liquid crystal display panel and multiple structural layers;

[0043] The extraction module is used to extract the defect region from the image corresponding to each target layer to obtain the defect region corresponding to each target layer.

[0044] The determination module is used to determine the target layer where the defect is located based on the salience of the defect region in the image corresponding to each target layer.

[0045] In one possible implementation of the second aspect, the control module is specifically used for:

[0046] Control the camera to move at a predetermined distance, so that the camera's focus point is on the upper surface layer, and take an image of the upper surface layer. After taking an image of the upper surface layer, control the camera to move towards the structural layers in sequence according to the physical distance between adjacent layers in each structural layer, and take an image of the camera when the focus point moves to each structural layer.

[0047] In one possible implementation of the second aspect, the acquisition module is specifically used for:

[0048] The image captured is taken at the first imaging position on the upper surface layer of the liquid crystal display panel when the camera's focus point is located on the upper surface layer, and the image captured when the camera's focus point moves to each structural layer.

[0049] In one possible implementation of the second aspect, the first imaging position is determined based on a predetermined optimal imaging distance between the camera and the upper surface layer of the liquid crystal display panel.

[0050] In one possible implementation of the second aspect, the extraction module is specifically used for:

[0051] For each target layer, image enhancement is performed on the image to obtain the enhanced image;

[0052] Defect regions are extracted from the enhanced image to obtain the first defect region;

[0053] The interference regions in the first defect region are filtered out to obtain the defect region corresponding to the target layer.

[0054] In one possible implementation of the second aspect, the determining module is specifically used for:

[0055] For each target layer from which defect regions are extracted, the ratio of the energy gradient of the defect region corresponding to the target layer to the energy gradient of the image corresponding to the target layer is determined; wherein, the ratio corresponding to each target layer is used to indicate the salience of the defect region in the image corresponding to the target layer;

[0056] The target layer corresponding to the largest ratio among the determined ratios is identified as the layer where the defect is located.

[0057] In one possible implementation of the second aspect, the determining module is further configured to:

[0058] If the defect is determined to be located in the liquid crystal layer, then based on the image of the liquid crystal layer, it is determined whether the defect is a missing LED chip;

[0059] If it is determined that the defect is located in another structural layer outside the liquid crystal layer, then the size of the defect is determined.

[0060] In one possible implementation of the second aspect, the determining module is further configured to:

[0061] If the defect is a liquid crystal layer defect, the image of the liquid crystal layer is separated into multiple single-channel images;

[0062] For each single-channel image, the defect region is extracted to obtain the corresponding defect region for each single-channel image;

[0063] Based on the area of ​​the defect region corresponding to each single-channel image, determine whether the defect is a missing LED bead.

[0064] Thirdly, embodiments of this application provide an electronic device, including: a memory and a processor, wherein the memory is used to store a computer program; and the processor is used to execute the method described in the first aspect or any embodiment of the first aspect when the computer program is invoked.

[0065] Fourthly, embodiments of this application provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in the first aspect or any embodiment of the first aspect.

[0066] It is understood that the beneficial effects of the second to fourth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here.

[0067] The technical solution provided in this application, when performing defect detection, acquires images of multiple target layers of a liquid crystal display panel captured by a camera, then extracts defects from the images and determines the layer where the defect is located. This allows for differentiation between whether the defect is located on the panel surface or inside the panel, thereby not only improving the accuracy of defect detection but also more accurately locating the layer where the defect is located. Attached Figure Description

[0068] Figure 1 This is a schematic diagram illustrating an application scenario for defect detection in a liquid crystal display panel, provided in an embodiment of this application.

[0069] Figure 2 A schematic flowchart illustrating a method for detecting defects in a liquid crystal display panel provided in an embodiment of this application;

[0070] Figure 3 A flowchart illustrating the defect region extraction process provided in an embodiment of this application;

[0071] Figures 4-6 This application provides schematic diagrams of some defect detection results for its embodiments.

[0072] Figure 7 This is a schematic diagram of the structure of the liquid crystal display panel defect detection device provided in the embodiments of this application;

[0073] Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0074] The embodiments of this application are described below with reference to the accompanying drawings. The terminology used in the implementation section of this application is only for explaining specific embodiments and is not intended to limit the application. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0075] Figure 1 This is a schematic diagram illustrating an application scenario for defect detection in a liquid crystal display panel, as provided in an embodiment of this application. Figure 1As shown, the devices involved in this application scenario may include: electronic device 100, motor 110, camera 120 and liquid crystal display panel 130.

[0076] In this embodiment, the electronic device 100 can be a non-portable device such as a desktop computer, or a portable device such as a handheld computer, smartphone, or laptop computer. The electronic device 100 can establish a communication connection with the motor 110 and the camera 120 to exchange data. The established communication connection can be wired or wireless, and this embodiment does not impose any particular limitation on it.

[0077] The motor 110 can be a stepper motor, a servo motor, a DC motor, etc. This application will use a stepper motor as an example for illustrative purposes.

[0078] The camera 120 can store captured images in its own memory, or it can transmit captured images to the electronic device 100 in real time via a communication connection established with the electronic device 100. The camera can shoot directly at the screen or at an angle to the screen; this embodiment uses shooting directly at the liquid crystal display panel as an example. The camera 120 is connected to the motor 110, and the movement of the camera 120 is driven by the motor 110. This application does not impose any particular limitation on the connection method between the camera 120 and the motor 110.

[0079] The liquid crystal display panel 130 is the liquid crystal display panel to be tested. During testing, the liquid crystal display panel 130 is lit up. The camera 120 can take pictures of the upper surface layer 131 of the liquid crystal display panel 130 directly. Then, driven by the motor 110, it moves towards the liquid crystal display panel 130 to capture the corresponding images of each layer inside the liquid crystal display panel 130.

[0080] Specifically, the liquid crystal display panel 130 may include, from top to bottom: a glass layer 132, an optical adhesive layer 133, a liquid crystal layer 134, and a thin film transistor layer 135. The upper surface layer 131 is the upper surface of the liquid crystal display panel, that is, the upper surface of the glass layer 132. The defect region 136 may exist in any structural layer or the upper surface layer of the liquid crystal display panel 130.

[0081] It is understood that the structure of a liquid crystal display panel may also include other layers. This embodiment uses a four-layer physical structure of glass layer, optical adhesive layer, liquid crystal layer and thin film transistor layer as an example for illustrative explanation.

[0082] The electronic device 100 can determine the layer where the defect is located based on the images of each layer captured by the camera 120.

[0083] It is understood that after the camera 120 captures an image, it can store it and subsequently import the image into the electronic device 100; alternatively, it can send the image to the electronic device in real time after it is captured. The motor 110 can be controlled by the electronic device 100 or by other devices. For ease of explanation, this embodiment of the application uses the example of the electronic device 100 driving the camera 120 to move via the motor 110 and acquiring images captured by the camera 120 in real time for illustrative purposes.

[0084] The following is a detailed explanation of the process by which electronic device 100 performs defect detection based on images captured by camera 120.

[0085] Figure 2 This is a schematic flowchart of the liquid crystal display panel defect detection method provided in the embodiments of this application, as shown below. Figure 2 As shown, the method may include the following steps:

[0086] S110: Acquire images taken by the camera for multiple target layers of the liquid crystal display panel.

[0087] The multiple target layers may include the upper surface layer of the liquid crystal display panel and multiple structural layers. These multiple structural layers may include all or part of the structural layers selected from glass, optical adhesive, liquid crystal, and thin film transistor layers. The following example illustrates the multiple structural layers including all of the structural layers selected from glass, optical adhesive, liquid crystal, and thin film transistor layers.

[0088] When the camera captures an image, it can first capture an image of the upper surface layer of the liquid crystal display panel at a first imaging position. At this first imaging position, the camera's focus point is located on the upper surface layer, and the quality of the captured image meets the target requirements, such as the image sharpness meeting the preset sharpness requirements.

[0089] The first imaging position can be the optimal imaging position determined for the current liquid crystal display panel under test; or it can be determined based on the optimal imaging distance of the upper surface layer of the liquid crystal display panel, wherein the liquid crystal display panel corresponding to the determination of the optimal imaging distance can be the current liquid crystal display panel under test or other liquid crystal display panels.

[0090] Specifically, the optimal imaging position and optimal imaging distance can be determined in the following way:

[0091] First, control the camera to move above the LCD panel at a preset distance and take pictures of the panel at different distances to obtain multiple images of the upper surface layer of the panel. Then, select the image with the best image quality from the multiple images of the upper surface layer, determine the camera position corresponding to the image with the best image quality as the optimal imaging position of the LCD panel, and determine the distance between the camera and the panel corresponding to the image with the best image quality as the optimal imaging distance of the LCD panel.

[0092] After acquiring the image of the upper surface layer, the camera can be controlled to move sequentially towards each structural layer based on the physical distance between adjacent layers in each target layer, and the image captured by the camera when the focal point moves to each structural layer can be obtained.

[0093] Electronic devices can drive camera movement by sending pulses to a motor. For example, after the electronic device controls the camera to capture an image at the first imaging position, it can move the motor for approximately 790 pulses to move the camera toward the liquid crystal display panel, focusing the camera on the glass layer and capturing an image of the glass layer. Then, the electronic device can move the motor for approximately 210 pulses to move the camera toward the liquid crystal display panel, focusing the camera on the optical adhesive layer and capturing an image of the optical adhesive layer. After that, the electronic device can move the motor for approximately 460 pulses to move the camera toward the liquid crystal display panel, focusing the camera on the liquid crystal layer and capturing an image of the liquid crystal layer. Finally, the electronic device can move the motor for approximately 480 pulses to move the camera toward the liquid crystal display panel, focusing the camera on the thin-film transistor layer and capturing an image of the thin-film transistor layer.

[0094] S120. Extract the defect region from the image corresponding to each target layer to obtain the defect region corresponding to each target layer.

[0095] The image of the defect location will differ from the image of the surrounding area. After obtaining the images corresponding to each target layer, the defect area can be extracted from each image using methods such as the difference method.

[0096] To improve the accuracy of the extraction results, the acquired image can be preprocessed before extracting the defect area. Figure 3 This is a flowchart illustrating the defect region extraction process provided in an embodiment of this application. For the image corresponding to each target layer, this can be used. Figure 3 The method shown is used to extract defect regions, such as Figure 3 As shown, the process may include the following steps:

[0097] S121. Perform image enhancement on the image corresponding to the target layer to obtain the enhanced image.

[0098] Specifically, when performing image enhancement, the image corresponding to the target layer can first be separated into multiple single-channel images, which may include an R-channel image, a G-channel image, and a B-channel image. Then, the individual single-channel images can be added together to obtain the enhanced image.

[0099] It is understood that other image enhancement algorithms can also be used for image enhancement, and this embodiment does not impose any particular limitations on this.

[0100] S122. Extract the defect region from the enhanced image to obtain the first defect region.

[0101] After obtaining the enhanced image, binarization or background subtraction can be performed on the enhanced image to extract the defect region. The extracted first defect region may be one, zero, or multiple. If no first defect region is extracted, subsequent steps S123 can be skipped.

[0102] S123. Filter out the interference areas in the first defect area to obtain the defect area corresponding to the target layer.

[0103] After extracting the first defect region, interference areas within the first defect region can be removed to improve the accuracy of the extraction results.

[0104] Specifically, the same algorithm can be used for each target layer, or different algorithms can be used to remove interference regions based on the characteristics of each target layer.

[0105] For the upper surface layer, morphological closing operations can be performed on its first defect area to obtain a relatively complete area. Then, interference areas can be removed by area filtering to obtain the corresponding defect area of ​​the layer.

[0106] For the glass layer, small spot interference can be removed by morphological top-hat operation, and then the interference area can be removed by area filtering to obtain the corresponding defect area of ​​the layer.

[0107] For optical adhesive layers, interference areas can be removed by area screening to obtain the corresponding defect areas of the layer.

[0108] For liquid crystal layers and thin-film transistor layers, edge interference can be removed by edge blurring, and then the defect regions can be obtained by clustering based on the defect area and distance.

[0109] S130. Determine the target layer where the defect is located based on the salience of the defect region in the image corresponding to each target layer.

[0110] The more obvious the defect is on the graph, the greater the energy gradient value of its defect region. Therefore, after obtaining the defect regions of each target layer, the significance of the defect regions of each target layer can be measured by the energy gradient, thereby determining the layer where the defect is located.

[0111] Specifically, for each target layer from which the defect region has been extracted, the ratio of the energy gradient of the defect region corresponding to that target layer to the energy gradient of the image corresponding to that target layer can be determined. Then, the layer containing the defect is determined based on this ratio for each target layer. The Energy of Gradient (EOG) function can be used to calculate the energy gradient of the defect region corresponding to each target layer and the energy gradient of the image corresponding to that target layer. The Energy of Gradient (EOG) function can be expressed by the following formula:

[0112]

[0113] Where f(x,y) is the gray value of the image at (x,y).

[0114] After calculating the ratio corresponding to each target layer using this function, the target layer with the largest ratio can be identified as the target layer where the defect is located.

[0115] It is understood that other parameters, such as average gradient, can also be used to measure the significance of the defect area, and this embodiment does not impose any particular limitation on this.

[0116] The following examples illustrate the defect detection results of this solution.

[0117] Example 1: See Figure 4 , Figure 4 This is a schematic diagram of a defect detection result provided in an embodiment of this application, wherein, Figure 4 (a) to (e) are schematic diagrams of the defect extraction results of the upper surface layer, glass layer, optical adhesive layer, liquid crystal layer and thin film transistor layer of the liquid crystal display panel, respectively.

[0118] Figure 4 In the upper surface layer shown in (a), the gradient energy value of the defect region is 15.398854, the gradient energy value of the image is 15.975778, and the normalized ratio is 0.963888.

[0119] Figure 4 In the glass layer shown in (b), the gradient energy value of the defect region is 15.252491, the gradient energy value of the image is 15.330215, and the normalized ratio is 0.994930.

[0120] Figure 4In the optical adhesive layer shown in (c), the gradient energy value of the defect region is 31.817099, the gradient energy value of the image is 15.840207, and the normalized ratio is 2.008629.

[0121] Figure 4 In the liquid crystal layer shown in (d), the gradient energy value of the defect region is 48.829288, the gradient energy value of the image is 57.247192, and the normalized ratio is 0.852955.

[0122] Figure 4 In the thin-film transistor layer shown in (e), the gradient energy value of the defect region is 25.794594, the gradient energy value of the image is 30.268812, and the normalized ratio is 0.852184.

[0123] Among the above ratios, the ratio corresponding to the optical adhesive layer is the largest. Therefore, it can be determined that the defect is located in the optical adhesive layer and is a defect of foreign matter adhesion. Figure 4 (f) in the diagram shows the minimum bounding rectangle of the defect, from which the size of the defect can be calculated. The data used to represent the size of the defect may include:

[0124] Defect size length (pixels): 483.069 pixels, defect size length (mm): 0.42027 mm;

[0125] Defect size width (pixels): 341.628 pixels, defect size width (mm): 0.297217 mm;

[0126] Defect dot diameter (pixels): 412.349 pixels, defect dot diameter (mm): 0.358743 mm;

[0127] Example 2: See Figure 5 , Figure 5 This is another schematic diagram of defect detection results provided in an embodiment of this application, wherein, Figure 5 Images (a) through (d) show the defect extraction results for the upper surface layer, glass layer, optical adhesive layer, and thin-film transistor layer of the liquid crystal display panel, respectively. No defect areas were detected in the liquid crystal layer.

[0128] Figure 5 In the upper surface layer shown in (a), the gradient energy value of the defect region is 19.402315, the gradient energy value of the image is 17.166140, and the normalized ratio is 1.130267.

[0129] Figure 5In the liquid crystal layer shown in (b), the gradient energy value of the defect region is 17.600941, the gradient energy value of the image is 16.633671, and the normalized ratio is 1.058151.

[0130] Figure 5 In the optical adhesive layer shown in (c), the gradient energy value of the defect region is 18.727070, the gradient energy value of the image is 17.884512, and the normalized ratio is 1.047111.

[0131] Figure 5 In the thin-film transistor layer shown in (d), the gradient energy value of the defect region is 26.499266, the gradient energy value of the image is 26.171886, and the normalized ratio is 1.012509.

[0132] Among the above ratios, the ratio corresponding to the upper surface layer is the largest. Therefore, it can be determined that the defect is located in the upper surface layer and is a non-real defect caused by the attached material.

[0133] Example 3: See Figure 6 , Figure 6 This is a schematic diagram of another defect detection result provided in an embodiment of this application, wherein, Figure 6 (a) to (e) are schematic diagrams of the defect extraction results of the upper surface layer, glass layer, optical adhesive layer, liquid crystal layer and thin film transistor layer of the liquid crystal display panel, respectively.

[0134] Figure 6 In the upper surface layer shown in (a), the gradient energy value of the defect region is 16.156775, the gradient energy value of the image is 16.303486, and the normalized ratio is 0.991001.

[0135] Figure 6 In the glass layer shown in (b), the gradient energy value of the defect region is 15.622214, the gradient energy value of the image is 15.718700, and the normalized ratio is 0.993862.

[0136] Figure 6 In the optical adhesive layer shown in (c), the gradient energy value of the defect region is 16.178598, the gradient energy value of the image is 17.244867, and the normalized ratio is 0.938169.

[0137] Figure 6 In the liquid crystal layer shown in (d), the gradient energy value of the defect region is 86.691757, the gradient energy value of the image is 80.713120, and the normalized ratio is 1.074072.

[0138] Figure 6In the thin-film transistor layer shown in (e), the gradient energy value of the defect region is 25.201572, the gradient energy value of the image is 24.229424, and the normalized ratio is 1.040123.

[0139] Among the above ratios, the ratio corresponding to the liquid crystal layer is the largest. Therefore, it can be determined that the defect is located in the liquid crystal layer. Figure 6 (f) in the figure shows the minimum bounding rectangle of the defect. Based on the implementation principle of the above method embodiment, the liquid crystal layer defect is determined to be a missing LED, specifically 1 green LED, 0 red LEDs, and 0 blue LEDs.

[0140] Those skilled in the art will understand that the above embodiments are exemplary and not intended to limit this application. Where possible, the execution order of one or more of the above steps can be adjusted, or they can be selectively combined to obtain one or more other embodiments. Those skilled in the art can arbitrarily select and combine the above steps as needed, and all those that do not depart from the essence of this application fall within the protection scope of this application.

[0141] The liquid crystal panel defect detection method provided in this embodiment allows the electronic device to acquire images of the upper surface layer and internal structural layers of the panel captured by a camera during panel defect detection. The defect area is extracted from the image, and the layer where the defect is located is determined. This distinguishes whether the defect is located on the panel surface or inside the panel, enabling layer-by-layer detection of the liquid crystal panel. This not only effectively improves the accuracy of defect detection but also allows for more accurate location of the layer where the defect is located.

[0142] Based on the same inventive concept, as an implementation of the above method, this application provides a liquid crystal display panel defect detection device. This device embodiment corresponds to the aforementioned method embodiment. For ease of reading, this device embodiment will not repeat the details of the aforementioned method embodiment one by one, but it should be clear that the device in this embodiment can correspondingly implement all the contents of the aforementioned method embodiment.

[0143] Figure 7 This is a schematic diagram of the structure of a defect detection device provided in an embodiment of this application, as shown below. Figure 7 As shown, the device provided in this embodiment may include: a control module 101, an acquisition module 102, an extraction module 103, and a determination module 104.

[0144] The control module 101 is used to control the camera to move at a predetermined distance, so that the camera's focus point is located on the upper surface layer, and to capture an image of the upper surface layer. The control module 101 controls the camera to move sequentially towards the structural layers according to the physical distance between adjacent layers in each structural layer, and to capture an image of the camera when the focus point moves to each structural layer.

[0145] The acquisition module 102 is used to acquire images taken by the camera at the first imaging position on the upper surface layer of the liquid crystal display panel when the camera's focus point is located on the upper surface layer, and to acquire images taken by the camera when the focus point moves to each structural layer.

[0146] The extraction module 103 is used to perform image enhancement on the image corresponding to each target layer to obtain an enhanced image, extract the defect region from the enhanced image to obtain the first defect region, and then filter out the interference region in the first defect region to obtain the defect region corresponding to the target layer.

[0147] The determination module 104 is used to measure the saliency of the defect region of each target layer by means of energy gradient for each target layer in which the defect region is extracted, and then determine the target layer with the largest saliency among the determined saliencies as the layer where the defect is located.

[0148] As an optional implementation of this application, the control module 101 is specifically used for:

[0149] Control the camera to move at a predetermined distance, so that the camera's focus point is on the upper surface layer, and take an image of the upper surface layer. After taking an image of the upper surface layer, control the camera to move towards the structural layers in sequence according to the physical distance between adjacent layers in each structural layer, and take an image of the camera when the focus point moves to each structural layer.

[0150] As an optional implementation of this application, the acquisition module 102 is specifically used for:

[0151] The image captured is taken at the first imaging position on the upper surface layer of the liquid crystal display panel when the camera's focus point is located on the upper surface layer, and the image captured when the camera's focus point moves to each structural layer.

[0152] As an optional implementation of this application, the first imaging position is determined based on a predetermined optimal imaging distance between the camera and the upper surface layer of the liquid crystal display panel.

[0153] As an optional implementation of this application, the extraction module 103 is specifically used for:

[0154] For each target layer, image enhancement is performed on the image to obtain the enhanced image;

[0155] Defect regions are extracted from the enhanced image to obtain the first defect region;

[0156] The interference regions in the first defect region are filtered out to obtain the defect region corresponding to the target layer.

[0157] As an optional implementation of this application, the determining module 104 is specifically used for:

[0158] For each target layer from which defect regions are extracted, the ratio of the energy gradient of the defect region corresponding to the target layer to the energy gradient of the image corresponding to the target layer is determined; wherein, the ratio corresponding to each target layer is used to indicate the salience of the defect region in the image corresponding to the target layer;

[0159] The target layer corresponding to the largest ratio among the determined ratios is identified as the layer where the defect is located.

[0160] As an optional implementation of this application, the determining module 104 is further configured to:

[0161] If the defect is determined to be located in the liquid crystal layer, then based on the image of the liquid crystal layer, it is determined whether the defect is a missing LED.

[0162] If it is determined that the defect is located in another structural layer outside the liquid crystal layer, then the size of the defect is determined.

[0163] As an optional implementation of this application, the determining module 104 is further configured to:

[0164] If the defect is a liquid crystal layer defect, the image of the liquid crystal layer is separated into multiple single-channel images;

[0165] For each single-channel image, the defect region is extracted to obtain the corresponding defect region for each single-channel image;

[0166] Based on the area of ​​the defect region corresponding to each single-channel image, determine whether the defect is a missing LED bead.

[0167] The defect detection device provided in this embodiment can execute the above method embodiment, and its implementation principle and technical effect are similar, so it will not be described again here.

[0168] Those skilled in the art will understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the functions described above can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0169] Based on the same inventive concept, embodiments of this application also provide an electronic device. Figure 8 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application, such as... Figure 8 As shown, the electronic device provided in this embodiment includes: a memory 210 and a processor 220. The memory 210 is used to store computer programs; the processor 220 is used to execute the method described in the above method embodiment when the computer program is invoked.

[0170] The electronic device provided in this embodiment can execute the above method embodiment, and its implementation principle and technical effect are similar, so they will not be described again here.

[0171] This application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the methods described in the above-described method embodiments.

[0172] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted through the computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, or magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)).

[0173] Those skilled in the art will understand that implementing all or part of the processes in the above embodiments can be accomplished by a computer program instructing related hardware. This program can be stored in a computer-readable storage medium, and when executed, it can include the processes described in the above method embodiments. The aforementioned storage medium can include various media capable of storing program code, such as ROM or random access memory (RAM), magnetic disks, or optical disks.

[0174] The naming or numbering of steps in this application does not imply that the steps in the method flow must be executed in the time / logical order indicated by the naming or numbering. The execution order of the named or numbered process steps can be changed according to the technical purpose to be achieved, as long as the same or similar technical effect can be achieved.

[0175] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0176] In the embodiments provided in this application, it should be understood that the disclosed apparatus / devices and methods can be implemented in other ways. For example, the apparatus / device embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0177] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0178] In the description of this application, unless otherwise stated, " / " indicates that the objects before and after are in an "or" relationship. For example, A / B can mean A or B. "And / or" in this application is merely a description of the relationship between the related objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist simultaneously, and B exists alone. A and B can be singular or plural.

[0179] Furthermore, in the description of this application, unless otherwise stated, "multiple" means two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0180] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if detected [the described condition or event]" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once detected [the described condition or event]," or "in response to detection [the described condition or event]."

[0181] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in a sequence other than that illustrated or described herein.

[0182] References described in this application, such as "one embodiment" or "some embodiments," mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized.

[0183] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A method for detecting defects in a liquid crystal display panel, characterized in that, The method includes: The camera captures images of multiple target layers of a liquid crystal display panel, including the upper surface layer and multiple structural layers of the liquid crystal display panel. For each target layer, the image is enhanced to obtain an enhanced image; The enhanced image is subjected to binarization or background subtraction to extract the defect region, thereby obtaining the first defect region; By filtering out the interfering regions in the first defect region, the defect region corresponding to the target layer is obtained; For each target layer from which defect regions are extracted, the ratio of the energy gradient of the defect region corresponding to the target layer to the energy gradient of the image corresponding to the target layer is determined; wherein, the ratio corresponding to each target layer is used to indicate the salience of the defect region in the image corresponding to the target layer; The target layer corresponding to the largest ratio among the determined ratios is identified as the layer where the defect is located.

2. The method according to claim 1, characterized in that, The acquisition of images captured by the camera targeting multiple target layers of the liquid crystal display panel includes: The image captured by the camera at a first imaging position onto the upper surface layer of the liquid crystal display panel is obtained. At the first imaging position, the focus point of the camera is located on the upper surface layer, and the quality of the captured image meets the target requirements. Based on the physical distance between adjacent layers in each target layer, the camera is controlled to move sequentially toward each structural layer to acquire images captured by the camera when the focal point moves to each structural layer.

3. The method according to claim 2, characterized in that, The first imaging position is determined based on the predetermined optimal imaging distance between the camera and the upper surface layer of the liquid crystal display panel.

4. The method according to any one of claims 1-3, characterized in that, The method further includes: If the defect is determined to be located in the liquid crystal layer, then based on the image of the liquid crystal layer, it is determined whether the defect is a missing LED. If it is determined that the defect is located in another structural layer outside the liquid crystal layer, then the size of the defect is determined.

5. The method according to claim 4, characterized in that, The step of determining whether the defect is a missing LED bead based on the image of the liquid crystal layer includes: Channel separation is performed on the image of the liquid crystal layer to obtain multiple single-channel images; For each single-channel image, the defect region is extracted to obtain the corresponding defect region for each single-channel image; Based on the area of ​​the defect region corresponding to each single-channel image, determine whether the defect is a missing LED bead.

6. A defect detection device for a liquid crystal display panel, characterized in that, include: The control module is used to control the camera to move according to the physical distance between adjacent layers in each structural layer, so that the camera's focus point is successively located on the upper surface layer and each structural layer, and to capture images of the upper surface layer and each structural layer. An acquisition module is used to acquire images captured by a camera targeting multiple target layers of a liquid crystal display panel, wherein the multiple target layers include the upper surface layer of the liquid crystal display panel and multiple structural layers; The extraction module is used to perform image enhancement on the image corresponding to each target layer to obtain an enhanced image; and to extract the defect region by performing binarization processing or background subtraction processing on the enhanced image to obtain a first defect region. And, filtering out the interfering regions in the first defect region to obtain the defect region corresponding to the target layer; The determination module is configured to, for each target layer from which the defect region has been extracted, determine the ratio of the energy gradient of the defect region corresponding to the target layer to the energy gradient of the image corresponding to the target layer; wherein the ratio corresponding to each target layer is used to indicate the salience of the defect region in the image corresponding to the target layer; and determine the target layer corresponding to the largest ratio among the determined ratios as the layer where the defect is located.

7. An electronic device, characterized in that, include: A memory and a processor, the memory being used to store a computer program; the processor being used to execute the method as described in any one of claims 1-5 when the computer program is invoked.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1-5.

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