Display panel abnormal color bright line detection method and device based on CCD sensing, equipment and storage medium

Abstract

This application discloses a method, apparatus, device, and storage medium for detecting off-color bright lines on a display panel based on CCD sensing, relating to the field of display panel detection technology. The method includes: acquiring an off-color image of the display panel under a preset color screen captured by the CCD imaging device; preprocessing the off-color image to obtain morphological feature images of different channels; performing line detection on each of the morphological feature images to obtain line feature information of different channels; and merging the line feature information of different channels to obtain a detection result. By employing multi-channel separation, morphological feature enhancement, and fusion detection techniques, this method solves the problems of uncertainty and weak contrast in existing detection methods when off-color bright lines appear under different color backgrounds, making stable identification difficult. Compared with existing technologies, it achieves high-sensitivity detection and precise positioning of off-color bright lines under different background colors, improving the accuracy and adaptability of the detection.

Description

Technical Field

[0001] This application relates to the field of display panel inspection technology, and in particular to a method, apparatus, device and storage medium for detecting off-color bright lines on display panels based on CCD (Charge-Coupled Device) sensing. Background Technology

[0002] With the rapid development of display panel technology, the requirements for display quality are increasing, especially for defects such as bright lines of different colors that only appear against a specific color background. These defects appear randomly when the panel displays different pure colors such as white, red, green, and blue, and their color and brightness are uncertain, which places higher technical demands on the sensitivity, stability, and adaptability of the detection methods.

[0003] Currently, most methods for detecting off-color bright lines on display panels employ traditional image processing techniques based on single-scale analysis or simple threshold segmentation. These methods are insensitive to subtle color differences and struggle to effectively capture off-color bright lines that are perceptible to the human eye but have weak contrast. Furthermore, they are susceptible to interference from factors such as panel texture and uneven imaging illumination, leading to high false detection rates, insufficient positioning accuracy, and a lack of universality for the defect characteristics of different panel types, making it difficult to reliably adapt to diverse inspection scenarios on production lines.

[0004] Therefore, how to provide a detection method that can adapt to different colored backgrounds, effectively extract faint heterochromatic bright line features, and accurately locate the position and size of defects has become an urgent technical problem to be solved in the current display panel manufacturing field.

[0005] The above content is only used to help understand the technical solution of this application and does not represent an admission that the above content is prior art. Summary of the Invention

[0006] The main objective of this application is to provide a method, apparatus, device, and storage medium for detecting off-color bright lines on display panels based on CCD sensing, aiming to solve the technical problem of how to improve the accuracy of off-color bright line detection on display panels.

[0007] To achieve the above objectives, this application proposes a method for detecting off-color bright lines in a display panel based on CCD sensing. The method is applied to the host computer of a CCD-sensing-based display panel off-color bright line detection system. The CCD-sensing-based display panel off-color bright line detection system includes a host computer, a CCD imaging device, a fixture board, and a display panel. The method includes:

[0008] Acquire the heterochromatic image of the display panel captured by the CCD imaging device under a preset color screen; The heterochromatic images are preprocessed to obtain morphological feature images of different channels; Line detection is performed on each of the morphological feature images to obtain line feature information for different channels; The linear feature information from the different channels is combined to obtain the detection result.

[0009] In one embodiment, acquiring the heterochromatic image of the display panel captured by the CCD imaging device under a preset color screen includes: The fixture board switches the color display screen according to the preset color control. When the display panel displays a color image corresponding to the preset color, the CCD imaging device is controlled to take a picture to obtain a different color image of the display panel under the preset color image.

[0010] In one embodiment, the preprocessing of the heterochromatic image to obtain morphological feature images of different channels includes: The heterochromatic image is split into images with different channels; Perform dual-scale Gaussian difference processing on the image of each channel to obtain the difference image corresponding to each channel; Image enhancement processing is performed on each of the difference images to obtain the corresponding morphological feature images for different channels.

[0011] In one embodiment, the dual-scale Gaussian difference processing of the image in each channel to obtain multiple difference images includes: Obtain a first-scale Gaussian kernel and a second-scale Gaussian kernel, wherein the size of the first-scale Gaussian kernel is larger than the size of the second-scale Gaussian kernel; Based on the first-scale Gaussian kernel, the image of each channel is subjected to first Gaussian blurring to obtain multiple first blurred images; The second Gaussian blurring process is applied to the image of each channel according to the second scale Gaussian kernel to obtain multiple second blurred images; A difference operation is performed on the first blurred image and the second blurred image in the same channel to obtain a difference image.

[0012] In one embodiment, the step of performing image enhancement processing on each of the difference images to obtain corresponding morphological feature images for different channels includes: Obtain the mean grayscale value of each of the difference images; Based on the corresponding grayscale mean of each of the difference images, contrast enhancement is performed on each of the difference images respectively; The enhanced difference images are processed sequentially by morphological opening and closing operations to obtain the morphological feature images corresponding to each channel.

[0013] In one embodiment, the process of performing line detection on each of the morphological feature images to obtain line feature information for different channels includes: Line detection is performed on each of the morphological feature images to obtain multiple candidate lines for each channel; Candidate lines for each channel are filtered according to a preset line length threshold to obtain the target line for each channel; The position and length information of the target straight line in each channel are extracted as the straight line feature information of the corresponding channel.

[0014] In one embodiment, after merging the linear feature information of the different channels to obtain the detection result, the method further includes: When the detection result indicates that the display panel has a defect, the target channel processing diagram is determined based on the linear characteristic information of different channels; Based on the linear feature information corresponding to the target channel processing image, mark the positions of bright lines in the heterochromatic image.

[0015] Furthermore, to achieve the above objectives, this application also proposes a CCD-based display panel color difference bright line detection device, the CCD-based display panel color difference bright line detection device comprising: The image acquisition module is used to acquire the heterochromatic image of the display panel under a preset color screen acquired by the CCD imaging device; The image processing module is used to preprocess the heterochromatic image to obtain morphological feature images of different channels; The line detection module is used to perform line detection on each of the morphological feature images to obtain line feature information of different channels; The result output module is used to merge the linear feature information of the different channels to obtain the detection result.

[0016] Furthermore, to achieve the above objectives, this application also proposes a display panel color difference bright line detection device based on CCD sensing. The device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor. The computer program is configured to implement the steps of the display panel color difference bright line detection method based on CCD sensing described above.

[0017] In addition, to achieve the above objectives, this application also proposes a storage medium, which is a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the steps of the display panel color difference bright line detection method based on CCD perception as described above.

[0018] In addition, to achieve the above objectives, this application also provides a computer program product, which includes a computer program that, when executed by a processor, implements the steps of the CCD-based display panel color-differential bright line detection method described above.

[0019] This application acquires a heterochromatic image of the display panel under a preset color screen, captured by the CCD imaging device; preprocesses the heterochromatic image to obtain morphological feature images of different channels; performs line detection on each of the morphological feature images to obtain line feature information of different channels; and merges the line feature information of different channels to obtain the detection result. By employing multi-channel separation, morphological feature enhancement, and fusion detection techniques, this application solves the problems of uncertainty and weak contrast in existing detection methods regarding heterochromatic bright lines appearing under different color backgrounds, which are difficult to reliably identify. Compared with existing technologies, this application achieves high-sensitivity detection and precise positioning of heterochromatic bright lines under different background colors, improving the accuracy and adaptability of the detection. Attached Figure Description

[0020] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0021] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a flowchart illustrating a first embodiment of the display panel color-differential bright line detection method based on CCD sensing in this application. Figure 2 This is a schematic diagram of the overall structure of the display panel color-differential bright line detection method based on CCD sensing provided in Embodiment 1 of this application; Figure 3 This is the output image of the detection result provided in Embodiment 1 of the display panel color-differential bright line detection method based on CCD sensing in this application; Figure 4 This is a flowchart illustrating Embodiment 2 of the display panel color-differential bright line detection method based on CCD sensing in this application. Figure 5 This is a single-channel processing flowchart provided in Embodiment 2 of the CCD-based display panel color bright line detection method of this application; Figure 6 This is a simplified flowchart of Embodiment 2 of the display panel color-differential bright line detection method based on CCD sensing provided in this application; Figure 7 This is a schematic diagram of the module structure of the display panel color-differential bright line detection device based on CCD sensing in an embodiment of this application; Figure 8 This is a schematic diagram of the device structure of the hardware operating environment involved in the CCD-based display panel color bright line detection method in the embodiments of this application.

[0023] Explanation of icon numbers: Host computer 01, CCD imaging equipment 02, fixture board 03, display panel 04.

[0024] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0025] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0026] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0027] The main solution of this application embodiment is: to acquire the heterochromatic image of the display panel under a preset color screen acquired by the CCD imaging device; to preprocess the heterochromatic image to obtain morphological feature images of different channels; to perform line detection on each of the morphological feature images to obtain line feature information of different channels; and to merge the line feature information of different channels to obtain the detection result.

[0028] In this embodiment, for ease of description, the host computer will be used as the execution subject in the following description.

[0029] Current methods for detecting off-color bright lines on display panels mostly employ traditional image processing techniques based on single-scale analysis or simple threshold segmentation. These methods are insensitive to subtle color differences and struggle to effectively capture off-color bright lines that are perceptible to the human eye but have weak contrast. Furthermore, they are susceptible to interference from factors such as panel texture and uneven imaging lighting, resulting in high false detection rates, insufficient positioning accuracy, and a lack of universality for the defect characteristics of different panel types, making it difficult to reliably adapt to diverse inspection scenarios on production lines.

[0030] This application provides a solution that employs multi-channel separation, morphological feature enhancement, and fusion detection techniques. This solves the problems of uncertainty and weak contrast in existing detection methods when different colored bright lines appear under different color backgrounds, making stable identification difficult. Compared with existing technologies, this solution achieves high-sensitivity detection and accurate positioning of different colored bright lines under different background colors, improving the accuracy and adaptability of detection.

[0031] It should be noted that the executing entity in this embodiment can be a computing service device with data processing, network communication, and program execution functions, such as a tablet computer, personal computer, or mobile phone, or an electronic device or host computer capable of performing the above functions. The following description uses a host computer as an example to illustrate this embodiment and the subsequent embodiments.

[0032] Based on this, embodiments of this application provide a method for detecting off-color bright lines on a display panel based on CCD sensing, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the display panel color-differential bright line detection method based on CCD sensing in this application.

[0033] Reference Figure 2 , Figure 2 This is a schematic diagram of the overall structure of the display panel color-differentiated bright line detection system based on CCD sensing, which is the first embodiment of the display panel color-differentiated bright line detection method based on CCD sensing of this application.

[0034] like Figure 2 As shown, the display panel color bright line detection system based on CCD sensing includes a host computer 01, a CCD imaging device 02, a fixture plate 03, and a display panel 04. The host computer 01 is connected to the CCD imaging device 02, and the fixture plate 03 is connected to the display panel 04.

[0035] It should be noted that the host computer 01 is a control and processing unit used to control the system operation and implement the detection algorithm; the CCD imaging device 02 is an image acquisition unit used to perform optical imaging on the display screen; the fixture board 03 is a signal driving unit used to output preset color image signals to the display screen; and the display panel 04 is the detection unit used to present the display screen to be detected.

[0036] Specifically, during the detection process, the host computer 01 sends instructions to the fixture plate 03, controlling the fixture plate 03 to drive the display panel 04 to sequentially switch and display four preset color images: white, red, green, and blue. The CCD imaging device 02 acquires images when each color image is stably displayed and transmits the acquired images to the host computer 01. The host computer 01 performs multi-channel separation, morphological processing, line detection, and information fusion algorithms on the received images, and finally outputs the detection result of whether the display panel has a defect of a different colored bright line.

[0037] In this embodiment, the method for detecting off-color bright lines on a display panel based on CCD sensing includes steps S10 to S40: Step S10: Obtain the heterochromatic image of the display panel under a preset color screen captured by the CCD imaging device; It should be noted that the preset color screen refers to the display content that is pre-set to trigger the bright line of the opposite color, typically including four pure color screens: white, red, green, and blue; the opposite color image refers to the image that contains lines with abnormal brightness or color in the corresponding screen when the preset color screen is displayed on the display panel due to the existence of the bright line defect of the opposite color.

[0038] It is understandable that, since the appearance of heterochromatic bright lines under different colored backgrounds is uncertain, acquiring only a single background image can easily lead to missed detections. Therefore, by controlling the display panel to switch and acquire images under multiple preset colored backgrounds in sequence, it is possible to cover different background conditions that heterochromatic bright lines may appear, thereby improving the completeness and reliability of defect detection.

[0039] In one feasible implementation, step S10 may include: controlling the fixture plate to switch the color screen of the display panel according to a preset color; and controlling the CCD imaging device to take a picture when the display panel displays the color screen corresponding to the preset color, so as to obtain a different color image of the display panel under the preset color screen.

[0040] It should be noted that the preset color refers to a pre-determined set of background colors used to trigger the detection, including white, red, green, and blue; the color screen refers to the display screen of the corresponding color presented by the display panel according to the color signal input from the fixture plate.

[0041] Specifically, the host computer 01 sends a color switching command to the fixture board, and the fixture board 03 generates a corresponding driving signal according to the command and outputs it to the display panel 04 to control it to switch to the specified color screen. After the screen stabilizes, the host computer 01 sends a shooting command to the CCD imaging device 02. The CCD imaging device 02 takes a picture of the current display screen and transmits the acquired digital image back to the host computer as a different color image under that color.

[0042] For example, the host computer 01 sends "white", "red", "green" and "blue" commands in sequence, and the fixture board drives the display panel 04 to display the corresponding solid color image in sequence. The CCD imaging device 02 takes an image during each image display period, thereby obtaining four images to be detected under different background colors.

[0043] In this embodiment, by adopting a multi-background triggering and synchronous acquisition mechanism, potential defect images can be acquired under different colored backgrounds, which solves the problem of missed detection of bright lines of different colors caused by uncertain background colors, and provides a complete image data foundation for subsequent accurate identification and positioning.

[0044] The above are merely feasible implementations of step S10 provided in this embodiment. This embodiment does not specifically limit the specific implementation of step S10.

[0045] Step S20: Preprocess the heterochromatic image to obtain morphological feature images of different channels; It should be noted that preprocessing refers to a series of image processing operations performed on the acquired heterochromatic images to enhance the contrast between heterochromatic bright lines and the background and suppress noise interference; channels refer to the monochrome component images obtained after decomposing the color image, typically including the red channel, green channel and blue channel; morphological feature images refer to binary or grayscale images obtained after morphological processing, which highlight the geometric structure and contour features in the image, in which heterochromatic bright lines are presented as connected, smooth lines.

[0046] Specifically, the preprocessing includes separating the heterochromatic image into three independent channel images: red, green, and blue; performing dual-scale Gaussian difference processing on each channel image to obtain a difference image highlighting local contrast changes; then performing contrast enhancement on each difference image based on its own grayscale mean; finally, performing morphological opening operations on the enhanced images to remove discrete noise, and then performing morphological closing operations to connect broken bright line contours, thereby obtaining the morphological feature images corresponding to each channel.

[0047] Understandably, since the contrast between bright lines of different colors and the background varies in different channels, processing only the original image or a single channel can easily lead to incomplete feature extraction. Therefore, by separating multiple channels and performing enhancement and morphological processing on each channel, the most prominent bright line features in each channel can be adaptively highlighted, avoiding feature loss or mis-extraction caused by improper channel selection or noise interference, thereby improving the accuracy and robustness of subsequent line detection.

[0048] Step S30: Perform line detection on each of the morphological feature images to obtain line feature information for different channels; It should be noted that line detection refers to the process of identifying and extracting connected pixel regions that satisfy the geometric features of a line from an image, and parameterizing them as line segments; the line feature information refers to structured data describing the geometric attributes of the detected line segments, including at least the position coordinates, length, and angle of the line segments in the image.

[0049] It is understandable that since morphological feature images may still contain non-target linear interference or broken bright line segments, it will be difficult to quantitatively analyze and accurately determine the different colored bright lines without targeted extraction and parameterization. Therefore, by performing line detection on each channel image separately, the geometric information of candidate bright lines can be accurately extracted from the enhanced feature image, avoiding interference from non-target structures, thereby improving the accuracy of defect localization and the reliability of the judgment basis.

[0050] In one feasible implementation, step S30 may include: performing line detection on each of the morphological feature images to obtain multiple candidate lines corresponding to each channel; filtering the candidate lines of each channel according to a preset line length threshold to obtain the target line of each channel; and extracting the position information and length information of the target line of each channel as the line feature information of the corresponding channel.

[0051] It should be noted that candidate lines refer to all possible line segments extracted from the image by the line detection algorithm; the preset line length threshold is a pre-set minimum length value used to distinguish effective bright lines of different colors from noise or short interference; the target line refers to the candidate line that meets the preset length condition after length screening, i.e., it is identified as a possible bright line of different colors; the position information refers to the starting and ending coordinates of the target line in the image coordinate system; the length information refers to the pixel length of the line segment calculated based on the starting and ending coordinates.

[0052] Specifically, for the morphological feature image of each channel, the Hough transform or line segment detection algorithm is used to extract all connected regions in the image that satisfy the straight line shape, and the endpoint coordinates of each straight line are output as the candidate straight line set for that channel. Then, each candidate straight line is traversed and its pixel length is calculated. If the length is greater than or equal to a preset length threshold, it is determined to be the target straight line. Finally, the start coordinates and end coordinates of each target straight line are extracted, and its length is calculated based on the coordinates. This information is organized into the straight line feature information set for that channel.

[0053] In this embodiment, a geometric screening mechanism is used to eliminate short interferences and extract linear structures with significant lengths, thus solving the problem of false detection caused by image noise or morphological residues, thereby achieving reliable identification and quantitative description of heterochromatic bright lines.

[0054] The above are merely feasible implementations of step S30 provided in this embodiment. This embodiment does not specifically limit the specific implementation of step S30.

[0055] Step S40: Merge the linear feature information of the different channels to obtain the detection result.

[0056] It should be noted that the test result refers to the final conclusion of whether the tested display panel has a defect of uneven bright lines. It is usually expressed as "qualified" or "unqualified" and may include the specific location and characteristic information of the defect.

[0057] Specifically, the straight line feature information of the red, green, and blue channels is summarized and merged; if a valid target straight line exists in the straight line feature information of any channel obtained after processing the corresponding image under any color screen (white, red, green, blue), the display panel is determined to be defective, and a poor detection result is output; if no valid target straight line is detected in any channel under all color screens, the display panel is determined to be qualified.

[0058] Understandably, since different colored bright lines appear differently on different colored backgrounds and in different channels, relying solely on a single channel or a single colored background for judgment can easily lead to missed detections. Therefore, by combining the detection information from all channels and all colored backgrounds for comprehensive judgment, it can be ensured that different colored bright lines can be identified under any conditions, avoiding missed detections due to condition limitations, thereby significantly improving the completeness and reliability of defect detection.

[0059] In one feasible implementation, step S40 may include: when the detection result indicates that the display panel has a defect, determining a target channel processing map based on the linear feature information of different channels; and marking the position of bright lines in the heterochromatic image based on the linear feature information corresponding to the target channel processing map.

[0060] It should be noted that the target channel processing image refers to the morphological feature image or difference image corresponding to the channel with the most obvious heterochromatic bright line feature in the color image where heterochromatic bright lines are detected; the bright line position refers to the coordinate region corresponding to the target straight line detected in the target channel processing image in the original heterochromatic image.

[0061] Specifically, when a defect is determined to exist in the display panel, the morphological feature image corresponding to the channel with the clearest target line and the most significant contrast is selected from all channels that detect the target line as the target channel processing image. Based on the coordinate information of the target line in the image, it is mapped back to the original image of the opposite color against the corresponding color background, and the specific location and range of the opposite color bright line are marked on the original image using graphic annotations (such as rectangles or highlight lines).

[0062] For example, such as Figure 3As shown, if a clear target line is detected in the morphological feature image of the green channel (G channel), then the green channel processed image is determined as the target channel processed image, and the coordinates of the line are mapped to the heterochromatic image with the original green background. A red line segment with the same position and length as the target line is drawn as the defect location label.

[0063] In this embodiment, by determining the optimal channel and mapping and labeling its position based on its feature information, the problems of poor interpretability of detection results and unintuitive defect location are solved, thereby realizing the visual location of defects and facilitating subsequent re-inspection and repair.

[0064] The above are merely feasible implementations of step S40 provided in this embodiment. This embodiment does not specifically limit the specific implementation of step S40.

[0065] This embodiment provides a method for detecting off-color bright lines on a display panel based on CCD sensing. The method involves acquiring an off-color image of the display panel under a preset color background, captured by a CCD imaging device; preprocessing the off-color image to obtain morphological feature images for different channels; performing line detection on each morphological feature image to obtain line feature information for different channels; and merging the line feature information from different channels to obtain the detection result. By employing multi-channel separation, morphological feature enhancement, and fusion detection techniques, this method solves the problems of uncertainty and unstable identification of off-color bright lines under different color backgrounds and weak contrast in existing detection methods. Compared with existing technologies, it achieves high-sensitivity detection and accurate positioning of off-color bright lines under different background colors, improving the accuracy and adaptability of the detection.

[0066] Based on the first embodiment of this application, in the second embodiment of this application, the content that is the same as or similar to that in the first embodiment described above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 4 The step S20 of the CCD-based display panel color difference bright line detection method further includes steps S21 to S23: Step S21: The heterochromatic image is split into images with different channels; Specifically, such as Figure 5 In step 2, the heterochromatic image is decomposed into color space to extract its red, green and blue components, thereby obtaining the corresponding red channel image, green channel image and blue channel image respectively.

[0067] Understandably, since the contrast of bright lines of different colors varies in different color channels, directly processing the original color image may not fully utilize the feature differences between the channels. Therefore, by separating the image into different channels, each channel can be analyzed independently, avoiding information confusion, thereby improving the sensitivity to subtle color differences and the accuracy of feature extraction.

[0068] Step S22: Perform dual-scale Gaussian difference processing on the image of each channel to obtain the difference image corresponding to each channel; It should be noted that dual-scale Gaussian difference processing is an image processing method that uses two Gaussian kernels of different scales to blur the same image and calculates the difference between the two blurred images to highlight features within a specific scale range in the image; the difference image corresponding to each channel refers to the image obtained after each channel image has undergone this processing, which reflects the local contrast changes.

[0069] Specifically, Gaussian blurring is performed on the image of each channel using a first-scale Gaussian kernel and a second-scale Gaussian kernel respectively, resulting in a corresponding first blurred image and a second blurred image. Then, the difference between the second blurred image and the first blurred image of each channel is calculated to obtain the difference image of that channel. In this image, the grayscale changes in the bright line regions of different colors are enhanced, while the background and slowly changing textures are suppressed.

[0070] It is understandable that since heterochromatic bright lines usually exhibit slight changes in local contrast and are easily affected by background texture, it is difficult to effectively distinguish them using only a single-scale analysis. Therefore, by using dual-scale Gaussian difference processing, feature differences at different scales can be extracted, avoiding the influence of background interference on target extraction, thereby improving the sensitivity and signal-to-noise ratio of heterochromatic bright lines.

[0071] In one feasible implementation, step S22 may include: obtaining a first-scale Gaussian kernel and a second-scale Gaussian kernel, wherein the size of the first-scale Gaussian kernel is larger than the size of the second-scale Gaussian kernel; performing a first Gaussian blurring process on the image of each channel according to the first-scale Gaussian kernel to obtain a plurality of first blurred images; performing a second Gaussian blurring process on the image of each channel according to the second-scale Gaussian kernel to obtain a plurality of second blurred images; and performing a difference operation on the first blurred image and the second blurred image of the same channel to obtain a difference image.

[0072] It should be noted that the first-scale Gaussian kernel is a large Gaussian filter used for strong smoothing of the image; the second-scale Gaussian kernel is a small Gaussian filter used for weak smoothing of the image; the first Gaussian blurring process refers to using the first-scale Gaussian kernel to perform a convolution operation on the image, resulting in a first blurred image with a high degree of smoothness; the second Gaussian blurring process refers to using the second-scale Gaussian kernel to perform a convolution operation on the image, resulting in a second blurred image with a lower degree of smoothness; the difference operation refers to performing a pixel-by-pixel numerical subtraction operation on two images.

[0073] Specifically, such as Figure 5 Step 3 involves performing Gaussian blurring twice on each input channel of the image, using Gaussian kernels of different sizes. The first Gaussian blurring uses a large kernel (kernel=61), denoted as strong filtering, producing the first blurred image, ground1. The second Gaussian blurring uses a smaller kernel (kernel=3), producing the second blurred image, ground2. Here, kernel represents the Gaussian kernel scale. By performing a difference operation on the two blurred images, ground2 and ground1, a difference image, sub, is obtained. This difference image reflects the changes in image content between small scales (small kernel) and large scales (large kernel), facilitating the processing of image features with weak contrast.

[0074] In this embodiment, by using Gaussian kernels of different scales to extract multi-scale features of the image and calculating their differences, weak and local linear features are effectively enhanced, solving the problem that traditional methods are insensitive to low-contrast heterochromatic bright lines.

[0075] The above are merely feasible implementations of step S22 provided in this embodiment. This embodiment does not specifically limit the specific implementation of step S22.

[0076] Step S23: Perform image enhancement processing on each of the difference images to obtain the corresponding morphological feature images for different channels.

[0077] It should be noted that image enhancement processing refers to adjusting the contrast and performing morphological operations on an image to further highlight target features and improve image quality.

[0078] Specifically, for the difference images of each channel, its own grayscale mean is first calculated, and then the image is contrast stretched based on the mean. After that, morphological opening operations are performed on the enhanced image to remove discrete noise points, and then morphological closing operations are performed to connect the broken bright line contours. Finally, the morphological feature images corresponding to each channel are obtained, in which the different colored bright lines are presented in the form of complete and clear lines.

[0079] Understandably, since the contrast of target features in the difference image may still be insufficient and may contain noise or breaks, direct line detection is prone to missed detections or false detections. Therefore, further contrast enhancement and morphological processing can improve the distinction between the target and the background and optimize the integrity of the lines, thereby improving the accuracy and stability of line detection.

[0080] In one feasible implementation, step S23 may include: obtaining the corresponding grayscale mean of each difference image; performing contrast enhancement on each difference image based on the corresponding grayscale mean of each difference image; and performing morphological opening and morphological closing operations on each enhanced difference image in sequence to obtain the morphological feature image corresponding to each channel.

[0081] It should be noted that grayscale mean refers to the arithmetic mean of the grayscale values ​​of all pixels in an image; contrast enhancement refers to the process of increasing the grayscale difference between features and the background by adjusting the distribution of pixel values ​​in the image; morphological opening operation refers to performing erosion operation followed by dilation operation, which is used to eliminate small noise and separate adhered targets; morphological closing operation refers to performing dilation operation followed by erosion operation, which is used to fill small holes and connect broken contours.

[0082] Specifically, for the difference image of each channel, its grayscale mean is calculated, and the image is linearly stretched based on the mean to enhance its contrast. Then, the enhanced image is first opened using a specific structuring element to remove discrete noise, and then closed using the same or different structuring elements to connect the interrupted parts of the bright lines. Finally, the binarized or grayscale morphological feature image corresponding to each channel is obtained, in which the different colored bright lines are highlighted as continuous and smooth lines.

[0083] For example, the first step is to perform image enhancement processing on the difference image sub to improve the visibility or contrast of features. For example... Figure 5 Step 4 in the formula is as follows:

[0084] Where dst represents the contrast-enhanced image, sub represents the difference image of each input channel, mean represents the grayscale mean, and scale represents the percentage of contrast enhancement.

[0085] The second step is to extract morphological features from each channel, such as lines and contours. For example... Figure 5 Step 5 of the test. The specific checks are as follows: After image contrast enhancement, noise in image dst is removed using an opening operation to obtain image dst1. The calculation formula is:

[0086] Where dst1 represents the image after the opening operation, src represents the input image dst, and B represents the structuring element.

[0087] The third step is to perform a closing operation to connect the disconnected lines, forming a complete straight line, thus obtaining the image dst2. The calculation formula is:

[0088] Where dst2 represents the image after the closing operation, dst1 represents the image after the opening operation, and B represents the structuring element.

[0089] In this embodiment, the visibility and structural integrity of the heterochromatic bright lines are effectively improved through adaptive contrast enhancement and morphological optimization, thus solving the problem of incomplete feature extraction caused by uncertain brightness or noise interference.

[0090] The above are merely feasible implementations of step S23 provided in this embodiment. This embodiment does not specifically limit the specific implementation of step S23.

[0091] This embodiment provides a method for detecting discolored bright lines on a display panel based on CCD sensing. The discolored image is split into images of different channels; each channel's image undergoes dual-scale Gaussian difference processing to obtain the corresponding difference image; and each difference image undergoes image enhancement processing to obtain the corresponding morphological feature images for each channel. By employing a combination of multi-channel independent analysis and dual-scale feature enhancement, this method solves the problems of traditional methods being insensitive to contrast changes in discolored bright lines under different color backgrounds and easily affected by background texture interference. This achieves highly robust feature extraction and enhancement for weak discolored bright lines, providing a high-quality image foundation for subsequent accurate detection.

[0092] For example, to help understand the implementation process of the CCD-sensing-based display panel color difference bright line detection method obtained in this embodiment combined with the above embodiment one, please refer to... Figure 6 , Figure 6 A simplified flowchart of a method for detecting off-color bright lines on a display panel based on CCD sensing is provided, specifically: The overall process begins with the fixture plate 03 sequentially controlling the display panel 04 to display four preset color images: white, red, green, and blue. For each color image, a camera (CCD imaging device 02) simultaneously captures an image of the display panel under that image, thus obtaining multiple images of the defect to be inspected containing potential heterochromatic bright lines against different color backgrounds. This step ensures that defects under different display conditions can be captured, providing a complete image data foundation for subsequent processing.

[0093] For each acquired image, an image processing procedure is performed: the image is split into three independent channels: red, green, and blue; each channel image is sequentially subjected to dual-scale Gaussian difference processing to enhance local contrast differences, resulting in the difference image corresponding to each channel; the difference image is then enhanced for contrast based on its own grayscale mean; subsequently, morphological opening and closing operations are used to further optimize features, remove noise, and connect broken contours, thereby generating the morphological feature image corresponding to each channel.

[0094] Line detection is performed on the morphological feature images of each channel under each color image, and the line feature information of each channel is extracted and filtered. The line feature information of all channels under all color images is summarized. If any channel in any image has a valid line feature, it is determined that there is a defect of bright line of different color on the display panel, and the defect location can be marked in the corresponding original image, thus completing the whole process of detection from image acquisition, feature extraction to defect judgment.

[0095] It should be noted that the above examples are only for understanding this application and do not constitute a limitation on the method for detecting different colored bright lines on a display panel based on CCD perception. Any simple modifications based on this technical concept are within the protection scope of this application.

[0096] This application also provides a display panel color difference bright line detection device based on CCD sensing, please refer to... Figure 7 The CCD-based display panel color difference bright line detection device includes: Image acquisition module 10 is used to acquire the heterochromatic image of the display panel under a preset color screen acquired by the CCD imaging device; Image processing module 20 is used to preprocess the heterochromatic image to obtain morphological feature images of different channels; The line detection module 30 is used to perform line detection on each of the morphological feature images to obtain line feature information of different channels; The result output module 40 is used to merge the linear feature information of the different channels to obtain the detection result.

[0097] The CCD-sensing-based display panel out-of-color bright line detection device provided in this application employs the CCD-sensing-based display panel out-of-color bright line detection method described in the above embodiments, and can solve the technical problem of how to improve the accuracy of out-of-color bright line detection in display panels. Compared with the prior art, the beneficial effects of the CCD-sensing-based display panel out-of-color bright line detection device provided in this application are the same as those of the CCD-sensing-based display panel out-of-color bright line detection method described in the above embodiments, and other technical features in the CCD-sensing-based display panel out-of-color bright line detection device are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0098] The image acquisition module 10 is also used to control the fixture plate to switch the color screen of the display panel according to the preset color; when the display panel displays the color screen corresponding to the preset color, it controls the CCD imaging device to take a picture to obtain the different color image of the display panel under the preset color screen.

[0099] The image processing module 20 is further configured to split the heterochromatic image into images of different channels; perform dual-scale Gaussian difference processing on the image of each channel to obtain the difference image corresponding to each channel; and perform image enhancement processing on each difference image to obtain the morphological feature image corresponding to each channel.

[0100] The image processing module 20 is further configured to obtain a first-scale Gaussian kernel and a second-scale Gaussian kernel, wherein the size of the first-scale Gaussian kernel is larger than the size of the second-scale Gaussian kernel; perform a first Gaussian blurring process on the image of each channel according to the first-scale Gaussian kernel to obtain multiple first blurred images; perform a second Gaussian blurring process on the image of each channel according to the second-scale Gaussian kernel to obtain multiple second blurred images; and perform a difference operation on the first blurred image and the second blurred image of the same channel to obtain a difference image.

[0101] The image processing module 20 is further configured to obtain the corresponding grayscale mean of each difference image; perform contrast enhancement on each difference image based on the corresponding grayscale mean of each difference image; and perform morphological opening and morphological closing operations on each enhanced difference image in sequence to obtain the morphological feature image corresponding to each channel.

[0102] The line detection module 30 is further configured to perform line detection on each of the morphological feature images to obtain multiple candidate lines corresponding to each channel; filter the candidate lines of each channel according to a preset line length threshold to obtain the target lines of each channel; and extract the position information and length information of the target lines of each channel as the line feature information of the corresponding channel.

[0103] The result output module 40 is further configured to, when the detection result indicates that the display panel has a defect, determine the target channel processing map based on the linear feature information of different channels; and mark the position of the bright line in the heterochromatic image based on the linear feature information corresponding to the target channel processing map.

[0104] This application provides a display panel color difference bright line detection device based on CCD sensing. The display panel color difference bright line detection device based on CCD sensing includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the display panel color difference bright line detection method based on CCD sensing in the first embodiment described above.

[0105] The following is for reference. Figure 8 This document illustrates a structural schematic diagram of a CCD-based display panel color-differential bright line detection device suitable for implementing embodiments of this application. The CCD-based display panel color-differential bright line detection device in this application embodiment can include, but is not limited to, mobile terminals such as mobile phones, laptops, digital radio receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Description), PMPs (Portable Media Players), and in-vehicle terminals (e.g., in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. Figure 8 The CCD-based display panel color difference detection device shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0106] like Figure 8As shown, the CCD-sensing-based display panel color difference bright line detection device may include a processing unit 1001 (e.g., a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in ROM (Read Only Memory) 1002 or a program loaded from storage device 1003 into random access memory (RRAM) 1004. The RAM 1004 also stores various programs and data required for the operation of the CCD-sensing-based display panel color difference bright line detection device. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to I / O interface 1006: input devices 1007 including, for example, touchscreens, touchpads, keyboards, mice, image sensors, microphones, accelerometers, gyroscopes, etc.; output devices 1008 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 1003 including, for example, magnetic tapes, hard disks, etc.; and communication devices 1009. Communication device 1009 allows the CCD-sensing-based display panel color difference bright line detection device to wirelessly or wiredly communicate with other devices to exchange data. Although the figure shows a CCD-sensing-based display panel color difference bright line detection device with various systems, it should be understood that it is not required to implement or possess all the systems shown. More or fewer systems can be implemented alternatively.

[0107] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from ROM 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0108] The CCD-sensing-based display panel out-of-color bright line detection device provided in this application employs the CCD-sensing-based display panel out-of-color bright line detection method described in the above embodiments, and can solve the technical problem of how to improve the accuracy of out-of-color bright line detection in display panels. Compared with the prior art, the beneficial effects of the CCD-sensing-based display panel out-of-color bright line detection device provided in this application are the same as those of the CCD-sensing-based display panel out-of-color bright line detection method described in the above embodiments, and other technical features in this CCD-sensing-based display panel out-of-color bright line detection device are the same as those disclosed in the previous embodiment method, and will not be repeated here.

[0109] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0110] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0111] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, which are used to execute the CCD-sensing-based method for detecting off-color bright lines on a display panel in the above embodiments.

[0112] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0113] The aforementioned computer-readable storage medium may be included in a CCD-based display panel color difference bright line detection device; or it may exist independently and not be assembled into a CCD-based display panel color difference bright line detection device.

[0114] The aforementioned computer-readable storage medium carries one or more programs. When these programs are executed by the CCD-based display panel color difference bright line detection device, the CCD-based display panel color difference bright line detection device performs the following actions: acquires a color difference image of the display panel under a preset color screen captured by the CCD imaging device; preprocesses the color difference image to obtain morphological feature images of different channels; performs line detection on each of the morphological feature images to obtain line feature information of different channels; and merges the line feature information of different channels to obtain a detection result.

[0115] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0116] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0117] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0118] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the above-described CCD-sensing-based method for detecting off-color bright lines on a display panel. This method can solve the technical problem of how to improve the accuracy of detecting off-color bright lines on a display panel. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the CCD-sensing-based method for detecting off-color bright lines on a display panel provided in the above embodiments, and will not be repeated here.

[0119] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the above-described method for detecting off-color bright lines on a display panel based on CCD perception.

[0120] The computer program product provided in this application can solve the technical problem of how to improve the accuracy of detecting off-color bright lines on display panels. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as those of the CCD sensing-based display panel off-color bright line detection method provided in the above embodiments, and will not be repeated here.

[0121] The above description is only a part of the embodiments of this application and does not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A method for detecting off-color bright lines on a display panel based on CCD sensing, characterized in that, The method is applied to the host computer of a CCD-based display panel color difference bright line detection system. The CCD-based display panel color difference bright line detection system includes a host computer, a CCD imaging device, a fixture plate, and a display panel. The method includes: Acquire the heterochromatic image of the display panel captured by the CCD imaging device under a preset color screen; The heterochromatic images are preprocessed to obtain morphological feature images of different channels; Line detection is performed on each of the morphological feature images to obtain line feature information for different channels; The linear feature information from the different channels is combined to obtain the detection result.

2. The method as described in claim 1, characterized in that, The step of acquiring the heterochromatic image of the display panel captured by the CCD imaging device under a preset color screen includes: The fixture board switches the color display screen according to the preset color control. When the display panel displays a color image corresponding to the preset color, the CCD imaging device is controlled to take a picture to obtain a different color image of the display panel under the preset color image.

3. The method as described in claim 1, characterized in that, The preprocessing of the heterochromatic image to obtain morphological feature images of different channels includes: The heterochromatic image is split into images with different channels; Perform dual-scale Gaussian difference processing on the image of each channel to obtain the difference image corresponding to each channel; Image enhancement processing is performed on each of the difference images to obtain the corresponding morphological feature images for different channels.

4. The method as described in claim 3, characterized in that, The image of each channel is subjected to dual-scale Gaussian difference processing to obtain multiple difference images, including: Obtain a first-scale Gaussian kernel and a second-scale Gaussian kernel, wherein the size of the first-scale Gaussian kernel is larger than the size of the second-scale Gaussian kernel; Based on the first-scale Gaussian kernel, the image of each channel is subjected to first Gaussian blurring to obtain multiple first blurred images; The second Gaussian blurring process is applied to the image of each channel according to the second scale Gaussian kernel to obtain multiple second blurred images; A difference operation is performed on the first blurred image and the second blurred image in the same channel to obtain a difference image.

5. The method as described in claim 3, characterized in that, The step of performing image enhancement processing on each of the difference images to obtain corresponding morphological feature images for different channels includes: Obtain the mean grayscale value of each of the difference images; Based on the corresponding grayscale mean of each of the difference images, contrast enhancement is performed on each of the difference images respectively; The enhanced difference images are processed sequentially by morphological opening and closing operations to obtain the morphological feature images corresponding to each channel.

6. The method as described in claim 1, characterized in that, The process of performing line detection on each of the morphological feature images to obtain line feature information for different channels includes: Line detection is performed on each of the morphological feature images to obtain multiple candidate lines for each channel; Candidate lines for each channel are filtered according to a preset line length threshold to obtain the target line for each channel; The position and length information of the target straight line in each channel are extracted as the straight line feature information of the corresponding channel.

7. The method as described in claim 1, characterized in that, After merging the linear feature information of the different channels to obtain the detection result, the method further includes: When the detection result indicates that the display panel has a defect, the target channel processing diagram is determined based on the linear characteristic information of different channels; Based on the linear feature information corresponding to the target channel processing image, mark the positions of bright lines in the heterochromatic image.

8. A device for detecting off-color bright lines on a display panel based on CCD sensing, characterized in that, The device includes: The image acquisition module is used to acquire the heterochromatic image of the display panel under a preset color screen acquired by the CCD imaging device; The image processing module is used to preprocess the heterochromatic image to obtain morphological feature images of different channels; The line detection module is used to perform line detection on each of the morphological feature images to obtain line feature information of different channels; The result output module is used to merge the linear feature information of the different channels to obtain the detection result.

9. A display panel color-shifting bright line detection device based on CCD sensing, characterized in that, The device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the CCD-sensing-based method for detecting off-color bright lines on a display panel as described in any one of claims 1 to 7.

10. A storage medium, characterized in that, The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, it implements the steps of the display panel color difference bright line detection method based on CCD perception as described in any one of claims 1 to 7.

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