High-resolution defect detection equipment and low-resolution defect detection method based on high-resolution defect detection equipment

Abstract

The invention provides high-resolution defect detection equipment and a low-resolution defect detection method based on the high-resolution defect detection equipment, and relates to the field of display detection. The defect detection module detects each frame of high-resolution image frame by frame so as to carry out micro-defect detection on the display panel to be detected, and the method comprises the following steps: the defect detection module compresses each frame of high-resolution image received by the defect detection module frame by frame to obtain a plurality of frames of low-resolution images, and sends the plurality of frames of low-resolution images to the detection control module; the detection control module carries out image processing at least including splicing on the received multiple frames of low-resolution images so as to obtain a low-resolution overall image of the display panel to be detected; and the detection control module performs low-resolution macroscopic defect detection on the display panel to be detected based on the low-resolution overall image, and high-resolution microdefect detection and low-resolution macroscopic defect detection are realized through a set of high-resolution defect detection equipment.

Description

Technical Field

[0001] This disclosure relates to the field of display inspection technology, specifically to a high-resolution defect detection device and a low-resolution defect detection method based thereon. Background Technology

[0002] In the manufacturing process of display panels, it is necessary to perform high-resolution micro-defect detection, such as but not limited to microcracks, as well as low-resolution macro-defect detection, such as but not limited to large-area patches. Related technologies provide two sets of cameras and defect detection equipment to perform the aforementioned high-resolution micro-defect detection and low-resolution macro-defect detection respectively. These two sets of equipment occupy a large space and are costly. Summary of the Invention

[0003] The main objective of this disclosure is to provide a high-resolution defect detection device and a low-resolution defect detection method based thereon, so as to achieve high-resolution micro-defect detection and low-resolution macro-defect detection through a set of high-resolution defect detection devices.

[0004] To achieve the above objectives, the first aspect of this disclosure provides a low-resolution defect detection method based on a high-resolution defect detection device, applied to defect detection of a display panel. The high-resolution detection device includes a scanning camera, a detection control module, and a defect detection module. The scanning camera is used to capture images frame by frame during the movement of the display panel to be inspected to acquire multiple frames of high-resolution images. Under the control of the detection control module, the defect detection module detects each frame of the high-resolution image to perform micro-defect detection on the display panel to be inspected. The low-resolution defect detection method includes: The defect detection module compresses each high-resolution image it receives frame by frame to obtain multiple low-resolution images, and sends the multiple low-resolution images to the detection control module. The detection control module performs image processing, including at least stitching, on the multiple frames of low-resolution images it receives to obtain a low-resolution overall image of the display panel to be detected; The detection control module performs low-resolution macroscopic defect detection on the display panel to be inspected based on a low-resolution overall image.

[0005] In some embodiments of this disclosure, the defect detection module compresses each received high-resolution image frame by frame to obtain multiple low-resolution images, including: The defect detection module calculates the number of frames and the theoretical low-resolution size of multiple low-resolution images based on the number of frames in multiple high-resolution images, the theoretical high-resolution size of each high-resolution image, and the target compression ratio. The defect detection module compresses each high-resolution image it receives into a low-resolution image with the same theoretical low-resolution size, based on the theoretical low-resolution size of each low-resolution image.

[0006] In some embodiments of this disclosure, the defect detection module compresses each received high-resolution image into a low-resolution image with a resolution equal to the theoretical low-resolution image size, based on the theoretical low-resolution image size of each low-resolution image, including: Average pooling convolution downsampling is used to compress each high-resolution image frame to obtain a low-resolution image with the theoretical low-resolution size.

[0007] In some embodiments of this disclosure, the defect detection module sends multiple frames of low-resolution images to the detection control module, including: Based on the number of frames in the multi-frame low-resolution image and the theoretical low-resolution size of each frame, an image template containing multiple subframes is pre-created. After compressing each high-resolution image received into a low-resolution image, the low-resolution image is written into the corresponding subframe of the image template. After the scanning camera completes the scan, it sends an image template consisting of multiple low-resolution images to the detection control module.

[0008] In some embodiments of this disclosure, the number of scanning cameras is at least two, and the at least two scanning cameras are arranged sequentially along a splicing direction perpendicular to the running direction of the display panel to be inspected; the number of defect detection modules is at least two, and each defect detection module corresponds to one scanning camera; and / or, the number of scans by the scanning camera is at least two, and the scanning field of view of the scanning camera is different in different scan processes. After all the scanning cameras have completed their scans, the detection control module performs image processing, including at least stitching, on all the image templates received from all the defect detection modules to obtain a low-resolution overall image of the display panel to be inspected.

[0009] In some embodiments of this disclosure, the detection control module performs image processing on all image templates, including at least stitching, to obtain a low-resolution overall image of the display panel to be detected, including: In a splicing direction where multiple image templates are parallel to the surface of the display panel to be inspected and perpendicular to the running direction of the display panel to be inspected, there is an overlapping area between two adjacent image templates; Based on the brightness information of the overlapping area between two adjacent image templates, the brightness of the two adjacent image templates is adjusted to the same brightness value.

[0010] In some embodiments of this disclosure, adjusting the brightness of two adjacent image templates to the same brightness value based on the brightness information of the overlapping area between two adjacent image templates includes: Use one of the two adjacent image templates as the reference image template and the other image template as the image template to be adjusted. Calculate the ratio of the mean gray level in the overlapping region of the adjusted image template to the mean gray level in the overlapping region of the reference image template; The mean ratio is used as a global gain coefficient when adjusting the brightness of the image template being adjusted, so that the brightness of two adjacent image templates is adjusted to the same brightness value.

[0011] In some embodiments of this disclosure, the detection control module performs image processing on all image templates, including at least stitching, to obtain a low-resolution overall image of the display panel to be detected, and further includes: During the process of stitching two adjacent image templates, the overlapping area of ​​one of the image templates is retained, while the overlapping area of ​​the other image template is removed. Based on the width of the retained overlapping region in the splicing direction and the centerline of the retained overlapping region parallel to the splicing direction, a gradual adjustment weight is determined to smoothly decrease from the centerline of the retained overlapping region to the centerline of the retained overlapping region away from the centerline of the retained overlapping region. The gradient adjustment weight is used as the adjustment weight for the grayscale value of each pixel in the retained overlapping region, and the grayscale value of each pixel in the retained overlapping region is adjusted.

[0012] In some embodiments of this disclosure, the detection control module performs image processing on all image templates, including at least stitching, to obtain a low-resolution overall image of the display panel to be detected, and further includes: Multiple image templates are stitched together sequentially from the first end of the stitching direction to the second end of the stitching direction, and adjacent image templates are stitched together to obtain a low-resolution overall image of the display panel to be tested. Specifically, when one of two adjacent image templates is used as the reference image template and the other image template is used as the image template to be adjusted, the image template closer to the first end of the splicing direction is used as the reference image template, and the image template closer to the second end of the splicing direction is used as the image template to be adjusted.

[0013] The second aspect of this disclosure provides a high-resolution defect detection device for defect detection of display panels. The high-resolution detection device includes a scanning camera, a detection control module, and a defect detection module. The scanning camera is used to capture images frame by frame during the movement of the display panel to be inspected to obtain multiple high-resolution images. Under the control of the detection control module, the defect detection module detects each high-resolution image frame by frame to perform micro-defect detection of the display panel to be inspected. The high-resolution defect detection device is also used to execute any of the low-resolution defect detection methods based on the high-resolution defect detection device provided in the first aspect of this disclosure.

[0014] The high-resolution defect detection device and low-resolution defect detection method based thereon provided in this disclosure configure a defect detection module and a detection control module based on the high-resolution defect detection device. The defect detection module compresses each frame of the high-resolution image it receives frame by frame to obtain multiple frames of low-resolution images, and sends the multiple frames of low-resolution images to the detection control module. The detection control module performs image processing on the multiple frames of low-resolution images it receives, including at least stitching, to obtain a low-resolution overall image of the display panel to be inspected. Based on the low-resolution overall image, it performs low-resolution macroscopic defect detection on the display panel to be inspected. Thus, a single high-resolution defect detection device can achieve high-resolution micro-defect detection and low-resolution macroscopic defect detection, eliminating the need for a separate camera and defect detection device. This not only reduces the space occupied by the defect detection device but also reduces the equipment cost. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the specific embodiments or related technologies of this disclosure, the accompanying drawings used in the description of the specific embodiments or related technologies will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 A schematic flowchart illustrating a low-resolution defect detection method based on a high-resolution defect detection device according to an embodiment of this disclosure; Figure 2 A top view of a high-resolution defect detection device provided in an embodiment of this disclosure; Figure 3 A schematic flowchart illustrating the process of micro-defect detection using a high-resolution defect detection device provided in an embodiment of this disclosure; Figure 4 A schematic flowchart illustrating the process of macroscopic defect detection using a high-resolution defect detection device provided in an embodiment of this disclosure; Figure 5This is a schematic diagram illustrating a process for compressing a high-resolution image into a low-resolution image according to an embodiment of the present disclosure. Figure 6 This is a schematic diagram illustrating the compression of a high-resolution image into a low-resolution image according to an embodiment of this disclosure; Figure 7 This is a schematic diagram illustrating the process of writing multiple frames of low-resolution images into an image template according to an embodiment of the present disclosure; Figure 8 This is a schematic diagram illustrating the writing of multiple low-resolution images into an image template according to an embodiment of the present disclosure; Figure 9 This is a schematic diagram of a detection control module receiving multiple image templates according to an embodiment of the present disclosure; Figure 10 This is a schematic diagram of the effective region divided in each image template according to an embodiment of the present disclosure; Figure 11 A schematic diagram illustrating the effective and overlapping regions divided in each image template according to an embodiment of this disclosure; Figure 12 This is a schematic diagram illustrating the process of adjusting the brightness of two adjacent image templates according to an embodiment of the present disclosure; Figure 13 This is a schematic diagram of a process for gradually adjusting the weight of overlapping regions according to an embodiment of the present disclosure; Figure 14 This is a schematic diagram illustrating the process of stitching multiple image templates into a low-resolution overall image, as provided in one embodiment of this disclosure.

[0017] Figure label: 101 - Display panel to be tested; 102 - Transmission device; 103 - First gantry 104-Second Gantry; 105-Alignment Camera; 1051-First Alignment Camera 1052 - Second Alignment Camera; 106 - Scanning Camera; 1061 - First Scanning Camera 1062 - Second Scan Camera; 1063 - Third Scan Camera 107-Detection and Control Module 108-Defect Detection Module 1081 - First Defect Detection Module; 1082 - Second Defect Detection Module 1083 - Third Defect Detection Module; 109 - Location and Result Verification Module Detailed Implementation To enable those skilled in the art to better understand the present disclosure, the technical solutions of the present disclosure will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of the present disclosure, and not all embodiments. Based on the embodiments of the present disclosure, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present disclosure.

[0018] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this disclosure 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 for the embodiments of this disclosure described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0019] In this disclosure, the terms “upper,” “lower,” “left,” “right,” “front,” “rear,” “top,” “bottom,” “inner,” “outer,” and “middle,” etc., indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings. These terms are primarily for the purpose of better describing this disclosure and its embodiments, and are not intended to limit the indicated devices, elements, or components to having a specific orientation, or to be constructed and operated in a specific orientation.

[0020] Furthermore, in addition to indicating location or positional relationship, some of the aforementioned terms may also have other meanings. For example, the term "above" may also be used in certain circumstances to indicate a dependency or connection. Those skilled in the art can understand the specific meaning of these terms in this disclosure according to the specific circumstances.

[0021] Furthermore, the terms "set up," "connect," and "link" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral structure; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection via an intermediate medium, or an internal connection between two devices, components, or parts. Those skilled in the art can understand the specific meaning of these terms in this disclosure according to the specific circumstances.

[0022] It should be noted that, unless otherwise specified, the embodiments and features described in this disclosure can be combined with each other. This disclosure will now be described in detail with reference to the accompanying drawings and embodiments.

[0023] In related technologies, Micro (high-magnification microscopic defect detection) inspection equipment is commonly used in the display panel manufacturing process to detect micron-level defects. These micro-defects can be, but are not limited to, point defects (black spots, bright spots), bright spots, microcracks, linear scratches, and pixel-level defects (such as OLED sub-pixel anomalies). The main technical characteristics of Micro inspection equipment are: extremely high resolution (e.g., 1–10 μm / pixel), large image pixels (300MP–1GP level), sensitivity to high-frequency information, and primarily processing localized, small targets.

[0024] In related technologies, Digital Mura (where Mura refers to brightness / color inconsistency defects caused by poor display uniformity, and Digital Mura refers to a low-resolution digitized large-area Mura distribution map) inspection equipment is commonly used in the display panel manufacturing process to detect macroscopic defects. Digital Mura equipment is a low-magnification, low-resolution, wide-field-of-view inspection system, mainly used for the detection of the following macroscopic defects: color banding, brightness drift, large-area patches, backlight unevenness, and large-size Mura (several centimeters to tens of centimeters).

[0025] Therefore, display panel manufacturing plants usually need two sets of defect detection equipment: Micro inspection equipment and Digital Mura equipment. Their disadvantages or deficiencies are mainly as follows: (1) Both sets of equipment are expensive, with high equipment purchase costs, large space occupation, and high maintenance costs; (2) The imaging mechanisms of Micro inspection equipment and Digital Mura inspection equipment are different, and they cannot be uniformly calibrated, resulting in: inconsistent detection results, inconvenient QA / engineering analysis, and difficulty in compliance assessment; (3) The low-resolution Digital Mura inspection equipment cannot reuse the original Micro data, and existing factories must re-acquire low-resolution images, resulting in: repeated exposure, repeated handling, and long repeated inspection time; (4) Low-frequency Mura defects and high-frequency point defects belong to different systems and are not easy to integrate for analysis.

[0026] Example 1 To address at least some of the aforementioned problems, this disclosure provides a low-resolution defect detection method based on a high-resolution defect detection device, applied to defect detection in display panels. This method falls under the cross-disciplinary fields of industrial visual inspection, multi-scale image processing, and frequency domain analysis. (Reference) Figure 2 and Figure 3The high-resolution inspection device includes a scanning camera 106, an inspection control module 107, and a defect detection module 108. The scanning camera 106 captures images frame by frame during the movement of the display panel 101 to be inspected, acquiring multiple high-resolution images. Under the control of the inspection control module 107, the defect detection module 108 inspects each high-resolution image frame by frame to perform micro-defect detection on the display panel 101 to be inspected. (Reference) Figure 1 The low-resolution defect detection method mainly includes the following steps: In step S110, the defect detection module 108 compresses each frame of the high-resolution image it receives frame by frame to obtain multiple frames of low-resolution images, and sends the multiple frames of low-resolution images to the detection control module 107. In step S120, the detection control module 107 performs image processing, including at least stitching, on the multiple frames of low-resolution images it receives to obtain a low-resolution overall image of the display panel 101 to be detected. In step S130, the detection control module 107 performs low-resolution macroscopic defect detection on the display panel 101 to be inspected based on the low-resolution overall image.

[0027] In the above scheme, the defect detection module 108 and the detection control module 107 are configured based on the high-resolution defect detection equipment. The defect detection module 108 compresses each frame of the high-resolution image it receives frame by frame to obtain multiple frames of low-resolution images, and sends the multiple frames of low-resolution images to the detection control module 107. The detection control module 107 performs image processing on the multiple frames of low-resolution images it receives, including at least stitching, to obtain a low-resolution overall image of the display panel 101 to be inspected. Based on the low-resolution overall image, it performs low-resolution macroscopic defect detection on the display panel 101 to be inspected. Thus, a set of high-resolution defect detection equipment can realize high-resolution micro-defect detection and low-resolution macroscopic defect detection. That is, by having the defect detection module 108 use a compression algorithm to compress and map the high-resolution image frame by frame into an equivalent low-resolution image, and then stitching the multiple frames of low-resolution images to obtain a low-resolution overall image of the display panel 101 to be inspected as an image reflecting low-frequency Mura defects for macroscopic defect detection, it is possible to use the Micro high-resolution defect detection equipment to simultaneously realize micro-defect detection and Digital Mura large-range low-frequency defect detection. By eliminating the need for a separate camera and defect detection equipment, the number of display-based defect detection devices is reduced, allowing a single high-resolution defect detection device to cover both Mura and Micro defect detection needs. This not only reduces the space occupied by defect detection equipment but also lowers equipment costs. This approach achieves a unified factory process, consistent inspection results, and reduced overall inspection costs. Furthermore, by using a depth model to simulate the "human eye's perception of Mura defects," the accuracy of defect detection is improved.

[0028] The following is in conjunction with the appendix Figures 1 to 14 The present disclosure provides a detailed description of the low-resolution defect detection method based on a high-resolution defect detection device.

[0029] For example, refer to Figure 2 The high-resolution defect detection device shown has a display panel 101 under the drive of the transmission device 102, with the edge of the panel being inspected moving as shown in the figure. Figure 2 The movement direction shown is left and right. A first gate 103 and a second gate 104 are arranged above the transmission device 102, spaced apart along the movement direction of the display panel 101 to be inspected. An alignment camera 105 is mounted on the first gate 103. The alignment camera 105 is used to position the display panel 101 to be inspected. The alignment camera 105 can be fixedly mounted on the first gate 103, so that the alignment camera 105 does not move relative to the first gate 103. The number of alignment cameras 105 can be one, two, or any number, as shown in the reference. Figure 2 The alignment camera 105 shown includes a first alignment camera 1051 and a second alignment camera 1052 that are spaced apart along the direction of motion perpendicular to the display panel 101 to be detected.

[0030] For example, refer to Figure 2 A scanning camera 106 is provided on the second gantry 104. Exemplarily, the scanning camera 106 can be a line scan camera, used to scan and photograph the display panel 101 to be inspected. The number of scanning cameras 106 can be one, two, or more. For example, refer to... Figure 2 The scanning camera 106 includes a first scanning camera 1061, a second scanning camera 1062 and a third scanning camera 1063 arranged along a direction perpendicular to the display panel 101 to be detected.

[0031] For example, refer to Figure 2 The second gantry 104 can move up and down to move closer to or further away from the display panel 101 to be tested. For example, refer to... Figure 2 When the display panel 101 to be inspected moves from the left side of the second gantry 104 to the right side of the second gantry 104, each scanning camera 106 completes its first scan. At this time, the second gantry 104 moves downward, and the display panel 101 to be inspected moves back to the left side of the second gantry 104, where each scanning camera 106 completes its second scan. The display panel 101 to be inspected reciprocates on the transmission device 102 until the scanning camera 106 completes its scan of the entire display panel 101.

[0032] For example, refer to Figure 2 and Figure 3During the scanning process of the scanning camera 106 scanning the display panel 101 to be inspected, the defect detection module 108 (such as...) Figure 3 The Inspector PC in the text refers to the defect detection module 108, which simultaneously performs Micro AOI inspection (high-resolution micro-defect detection) frame by frame. One frame represents one image; for example, one frame can represent a 16K image, specifically 16384. An image of 1024 pixels. For example, refer to... Figure 2 and Figure 3 In high-resolution defect detection equipment, the image resolution of each scanning camera 106 is typically 1~10 micrometers / pixel.

[0033] For example, refer to Figure 2 It also includes a positioning and result review module 109, which interacts with the control and detection module based on the positioning information of the alignment camera 105 to complete the review of the detection results by taking pictures with the Review camera (a review camera with higher resolution).

[0034] refer to Figure 4 During the process of receiving each high-resolution image scanned by the scanning camera 106 and performing micro-defect detection, the defect detection module 108 also compresses each high-resolution image received frame by frame to obtain multiple low-resolution images, and sends the multiple low-resolution images to the detection control module 107. The defect detection module 108 can compress each high-resolution image received frame by frame to obtain multiple low-resolution images in various ways, some of which are exemplified below.

[0035] For example, refer to Figure 5 The defect detection module 108 compresses each received high-resolution image frame by frame to obtain multiple low-resolution images. This can include: the defect detection module 108 calculating the number of low-resolution images and the theoretical low-resolution size of each low-resolution image based on the number of high-resolution images, the theoretical high-resolution size of each high-resolution image, and the target compression ratio; and the defect detection module 108 compressing each received high-resolution image into a low-resolution image with a resolution equal to the theoretical low-resolution size based on the theoretical low-resolution size. This allows for precise control of the actual resolution of the low-resolution images.

[0036] For example, refer to Figure 6The size of a low-resolution image compressed from a high-resolution image obtained by a single scan of the scanning camera 106 can be calculated. Before the high-resolution defect detection equipment performs a scan using the scanning camera 106, the theoretical low-resolution size of the compressed low-resolution image is calculated based on the theoretical high-resolution size of the high-resolution image and the target compression ratio. For example, if a complete scan requires scanning 700 frames, and each frame is 16384 pixels wide and 1024 pixels high (where the width of each frame is perpendicular to the direction of movement of the display panel 101 under inspection, and the height of each frame is parallel to the direction of movement of the display panel 101 under inspection), then the size of a complete scan of the high-resolution image is: width = 16384 pixels, height = 1024 pixels. 700 pixels. Assuming a target compression ratio of 128, the theoretical low-resolution image size after compression is: width = 16384 / 128 = 128 pixels, height = 1024 pixels. 700 / 128 = 5600 pixels.

[0037] For example, the defect detection module 108 compresses each received high-resolution image into a low-resolution image with the theoretical low-resolution size based on the theoretical low-resolution size of each low-resolution image. This can include: using average pooling convolution downsampling to compress each high-resolution image to obtain a low-resolution image with the theoretical low-resolution size, thereby maintaining the uniformity of the compressed image.

[0038] For example, the specific implementation of compression can be as follows: average pooling convolution downsampling is used. A single high-resolution image can be defined as X, the pooling window size can be k × k, that is, compressed by a factor of k, the pooling stride=k, and the low-resolution image output by average pooling can be defined as Y. Then, the pixel value of each pixel in the low-resolution image Y can be calculated using the following formula:

[0039] Where i+u = (k–i)×stride, j+v = (k–j)×stride. It should be noted that average pooling convolution downsampling differs from traditional downsampling; average pooling convolution downsampling can better maintain the uniformity of the compressed image.

[0040] For example, refer to Figure 7The defect detection module 108 sends multiple frames of low-resolution images to the detection control module 107. This process may include: pre-creating an image template containing multiple sub-frames based on the number of frames and the theoretical low-resolution size of each low-resolution image; compressing each high-resolution image received into a low-resolution image and writing the low-resolution image into the corresponding sub-frame of the image template; and sending the image template composed of multiple low-resolution images to the detection control module 107 after the scanning camera 106 completes the scan. By sending multiple frames of low-resolution images to the detection control module 107 in this manner, based on the scanning field of view of the scanning camera 106 each time, complete image information of the display panel 101 under the detection direction from one side to the other in the direction of movement can be obtained, simplifying the difficulty of stitching together multiple low-resolution images.

[0041] For example, refer to Figure 8 The diagram illustrates the compression of a high-resolution image into a low-resolution image. First, a black image template A is created in advance based on the previously calculated size of the low-resolution image. Image template A contains multiple subframes. Then, during the micro-defect detection process in the defect detection module 108 (i.e., when the high-resolution defect detection device starts running the scanning camera 106 to scan the display panel 101 to be inspected), each frame of the high-resolution image received from the detection control module 107 is compressed frame by frame using a multi-threaded process, and each compressed low-resolution image is written into the corresponding subframe of image template A.

[0042] For example, refer to Figure 2 The number of scanning cameras 106 can be at least two, and at least two scanning cameras 106 are arranged sequentially along a splicing direction perpendicular to the running direction of the display panel 101 to be inspected. (Reference) Figure 3 and Figure 4 The number of defect detection modules 108 is at least two, and each defect detection module 108 corresponds to one scanning camera 106. For example, refer to... Figure 2 , Figure 3 and Figure 4 The defect detection module 108 includes a first defect detection module 1081 corresponding to the first scanning camera 1061, a second defect detection module 1082 corresponding to the second scanning camera 1062, and a third defect detection module 1083 corresponding to the third scanning camera 1063. For example, refer to... Figure 2 As described above, the scanning camera 106 can perform at least two scans, and the scanning field of view of the scanning camera 106 is different in different scanning processes, that is, the scanning field of view of the scanning camera 106 can be adjusted.

[0043] For example, after all the scanning cameras 106 have completed their scans, the detection control module 107 performs image processing, including at least stitching, on all the image templates received from all the defect detection modules 108 to obtain a low-resolution overall image of the display panel 101 to be inspected.

[0044] For example, each defect detection module 108 sends its image template, obtained from compressed multi-frame low-resolution images, to the detection control module 107 in units of the number of scans. For example, each defect detection module 108 processes a high-resolution image from a scanning camera 106 (performing micro-defect detection and compressing the high-resolution image into a low-resolution image frame by frame). Each scanning camera 106 performs 3 scans. Therefore, the defect detection module 108 needs to send the image template, composed of compressed multi-frame low-resolution images obtained from the 3 scans, to the detection control module 107. After all the image templates obtained from all the scans by all the defect detection modules 108 have been sent, the detection control module 107 can then perform the complete splicing of the display panel 101 to be inspected.

[0045] The detection control module 107 can perform the complete stitching of the display panel 101 to be detected in the following ways. In some embodiments, two scanning cameras 106 are needed to complete the scanning of the entire display panel 101 to be detected. Each scanning camera 106 performs two scans, for a total of 2×2=4 scans, thereby obtaining four image templates composed of compressed multi-frame low-resolution images. For example, refer to Figure 9 The four image templates shown are image template A, image template B, image template C, and image template D.

[0046] For example, the detection control module 107 performs image processing on all image templates, including at least stitching, to obtain a low-resolution overall image of the display panel 101 to be detected. This may include: having an overlapping area between two adjacent image templates in a stitching direction that is parallel to the surface of the display panel 101 to be detected and perpendicular to the running direction of the display panel 101; and adjusting the brightness of the two adjacent image templates to the same brightness value based on the brightness information of the overlapping area between the two adjacent image templates, so that the brightness of the final stitched low-resolution overall image remains consistent.

[0047] For example, refer to Figure 9 The area within the yellow dashed box shown represents an image template composed of multiple compressed low-resolution images from a single scan. (Reference) Figure 10 The area within the red dashed box shown represents the effective area of ​​a single scan, indicating the directly usable display panel area. This effective area is calculated based on the hardware configuration of the scanning camera 106 and target compression comparison. (Reference) Figure 11The blue areas in the image represent overlapping regions between two adjacent image templates. Based on the brightness information of these overlapping regions, the brightness of the two adjacent image templates needs to be adjusted to the same value to ensure consistent brightness in the final stitched low-resolution overall image.

[0048] Based on the brightness information of the overlapping area between two adjacent image templates, there are various ways to adjust the brightness of two adjacent image templates to the same brightness value. Some of these methods are illustrated below.

[0049] For example, adjusting the brightness of two adjacent image templates to the same brightness value based on the brightness information of the overlapping area between two adjacent image templates may include: using one of the two adjacent image templates as a reference image template and the other image template as the image template to be adjusted; calculating the ratio of the mean gray value in the overlapping area of ​​the image template to the mean gray value in the overlapping area of ​​the reference image template; using the ratio as a global gain coefficient when adjusting the brightness of the image template to adjust the brightness of the image template to make the brightness of the two adjacent image templates the same brightness value.

[0050] For example, a mean-matching method can be used to perform global linear brightness adjustment. Since the environment is inconsistent with each scan during the actual generation of high-resolution images by the scanning camera 106, and light is highly sensitive, the brightness of the image templates obtained from each scan is inconsistent. Therefore, it is necessary to adjust the overall brightness to ensure that the final stitched low-resolution overall image has consistent brightness.

[0051] For example, refer to Figure 11 The overlapping region can be defined as R. Assuming that the brightness of the overlapping region R is uniform, the average gray value of two adjacent image templates within the overlapping region R can be calculated. The average gray value of the overlapping region of the two adjacent image templates (used as the reference image template) is then calculated and divided by the average gray value of the overlapping region of the image template being adjusted. The resulting ratio k is used as the global gain coefficient between the two adjacent image templates, where: I ref Indicates the reference image template (tone baseline), I Current R represents the image template being adjusted, and R represents the overlapping region (mask or set of coordinates). The formula for calculating the mean ratio k is as follows:

[0052] The adjusted image template I is obtained after adjusting the image template. adjusted as follows:

[0053] For example, refer to Figure 12 The detection control module 107 performs image processing on all image templates, including at least stitching, to obtain a low-resolution overall image of the display panel 101 to be detected. It may also include: during the stitching of two adjacent image templates, retaining the overlapping area of ​​one of the image templates and removing the overlapping area of ​​the other image template; based on the width of the retained overlapping area in the stitching direction and the center line of the retained overlapping area parallel to the stitching direction, determining a gradient adjustment weight that smoothly decays from the center line of the retained overlapping area to the direction away from the center line of the retained overlapping area; using the gradient adjustment weight as the adjustment weight for adjusting the grayscale value of each pixel in the retained overlapping area, thereby adjusting the grayscale value of each pixel in the retained overlapping area to avoid abruptness in global adjustment.

[0054] For example, weighted mean matching can be used for a gradual transition. To avoid abrupt changes in the global adjustment, a gradual weight is introduced in the overlapping region, causing the adjustment intensity to smoothly decay outward from the centerline parallel to the splicing direction within the preserved overlapping region. The gradual adjustment weight can include a weight function w(x,y) as follows, with the formula:

[0055] Among them, R center σ represents the centerline coordinates of the overlapping area parallel to the splicing direction, and σ represents the width of the overlapping area in the splicing direction, which can be used as a parameter to control the transition width.

[0056] For example, the gradual adjustment weights k(x,y) can be determined based on the weight function w(x,y) as follows:

[0057] Then, the gradient adjustment weight is used as the adjustment weight for the grayscale value of each pixel in the retained overlapping region. The adjusted image I is obtained after adjusting the grayscale value of each pixel in the retained overlapping region. adjusted (x,y) are as follows:

[0058] For example, refer to Figure 14The detection control module 107 performs image processing on all image templates, including at least splicing, to obtain a low-resolution overall image of the display panel 101 to be detected. It may also include: splicing multiple image templates from the first end of the splicing direction to the second end of the splicing direction, sequentially splicing two adjacent image templates to obtain a low-resolution overall image of the display panel 101 to be detected; wherein, when one of the two adjacent image templates is used as the reference image template and the other image template is used as the image template to be adjusted, the image template closer to the first end of the splicing direction is used as the reference image template, and the image template closer to the second end of the splicing direction is used as the image template to be adjusted.

[0059] For example, refer to Figure 14 The stitching process shown takes image templates A, B, C, and D as an example. First, image templates A and B are stitched together, with template A serving as the reference template and template B as the template to be adjusted. Next, the stitched image is stitched with image template C, again with template B serving as the reference template and C as the template to be adjusted. Finally, the stitched image is stitched with image template D to obtain a low-resolution overall image, with template C serving as the reference template and D as the template to be adjusted.

[0060] Afterwards, refer to Figure 1 The detection control module 107 performs low-resolution macroscopic defect detection on the display panel 101 to be inspected based on a low-resolution overall image, referencing... Figure 4 The detection control module 107 performs Mura defect detection on the display panel.

[0061] In the various embodiments shown above, a method is provided to generate an equivalent low-resolution overall image that can be used for large defect detection by using the original high-resolution image of a high-resolution micro-defect detection device through multi-scale image compression, block mean mapping, frequency domain low-pass filtering, multi-resolution fusion, etc., and finally realizing integrated detection of large and micro defects.

[0062] As can be seen from the above description, this disclosure achieves the following technical effects: For the first time, a defect-preserving model combining detection domain knowledge is used, ensuring that the compressed image fully meets the detection requirements of macroscopic defect detection equipment. Therefore, a single device can fulfill two tasks: micro-defects and macroscopic defects are uniformly detected on the same high-resolution defect detection device, achieving "dual-function in one machine." Furthermore, a multi-scale algorithm utilizing high-resolution images to generate equivalent low-resolution overall images eliminates the need for separate macroscopic defect detection hardware.

[0063] Since only one Micro device (high-resolution defect detection device) is needed, there is no need to add a separate Digital Mura device, reducing equipment costs (by more than 50%), maintenance and calibration costs, and significantly lowering engineering costs. All data comes from the same high-resolution defect detection device, so differences between devices on different production lines no longer affect the detection results, improving detection consistency.

[0064] A single image capture during micro-defect detection yields both high-resolution results and a low-resolution compressed image in Digital Mura style, eliminating the need for multiple captures and improving production line efficiency. This is achieved with a scanning resolution of 2µm / pixel and a 1500mm² display panel to be inspected. At 925mm, Micro+Digital Mura (micro-defects + macro-defects) inspection is completed simultaneously, and the entire process takes only 2 minutes, significantly reducing the inspection time.

[0065] The image compression process described above is not simply scaling; it preserves the macroscopic defect trend (blocky Mura), suppresses minute noise, and ensures that the contrast / brightness distribution fully conforms to the Digital Mura standard, thus better meeting inspection requirements. Through this compression, the true area of ​​the high-resolution image can be traced back from the low-resolution overall image (Digital Mura image), resulting in stronger data traceability.

[0066] Example 2 This disclosure provides a high-resolution defect detection device for defect detection of a display panel. The high-resolution detection device includes a scanning camera 106, a detection control module 107, and a defect detection module 108. The scanning camera 106 is used to capture images frame by frame during the movement of the display panel 101 to be inspected to obtain multiple high-resolution images. Under the control of the detection control module 107, the defect detection module 108 detects each high-resolution image frame by frame to perform micro-defect detection of the display panel 101 to be inspected. The high-resolution defect detection device is also used to execute any of the low-resolution defect detection methods based on the high-resolution defect detection device provided in the first aspect of this disclosure.

[0067] It should be noted that, in addition to the above-described structure, the high-resolution defect detection device in this embodiment may also include the related structures described in part of the embodiment, all of which are within the protection scope of the high-resolution defect detection device provided in this embodiment.

[0068] Although embodiments of the present disclosure have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the present disclosure, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A low-resolution defect detection method based on a high-resolution defect detection device, applied to defect detection of display panels, characterized in that, The high-resolution inspection device includes a scanning camera, an inspection control module, and a defect detection module. The scanning camera is used to capture images frame by frame during the movement of the display panel to be inspected to obtain multiple high-resolution images. The defect detection module, under the control of the inspection control module, detects each frame of the high-resolution image to perform micro-defect detection on the display panel to be inspected. The low-resolution defect detection method includes: The defect detection module compresses each frame of the high-resolution image it receives frame by frame to obtain multiple frames of low-resolution images, and sends the multiple frames of low-resolution images to the detection control module. The detection control module performs image processing, including at least stitching, on the received multi-frame low-resolution images to obtain a low-resolution overall image of the display panel to be detected. The detection control module performs low-resolution macroscopic defect detection on the display panel to be inspected based on the low-resolution overall image.

2. The method as described in claim 1, characterized in that, The defect detection module compresses each frame of the high-resolution image it receives frame by frame to obtain multiple frames of low-resolution images, including: The defect detection module calculates the number of frames and the theoretical low-resolution size of the multiple low-resolution images based on the number of frames of the multiple high-resolution images, the theoretical high-resolution size of each high-resolution image, and the target compression ratio. The defect detection module compresses each of the high-resolution images it receives into a low-resolution image with a resolution size equal to the theoretical low-resolution size, based on the theoretical low-resolution size of each low-resolution image.

3. The method as described in claim 2, characterized in that, The defect detection module, based on the theoretical low-resolution size of each frame of low-resolution image, compresses each received high-resolution image into a low-resolution image with a resolution size equal to the theoretical low-resolution size, including: The high-resolution image is compressed in each frame using average pooling convolution downsampling to obtain a low-resolution image with the same resolution as the theoretical low-resolution image.

4. The method as described in claim 2, characterized in that, The defect detection module sends the multiple frames of low-resolution images to the detection control module, including: Based on the number of frames of the multi-frame low-resolution images and the theoretical low-resolution size of each frame of low-resolution images, an image template containing multiple sub-frames is pre-created; After compressing each frame of the high-resolution image received into the low-resolution image, the low-resolution image is written into the corresponding subframe of the image template; After the scanning camera completes the scan, it sends an image template composed of the multiple low-resolution images to the detection control module.

5. The method as described in claim 4, characterized in that, The number of scanning cameras is at least two, and the at least two scanning cameras are arranged sequentially along a splicing direction perpendicular to the running direction of the display panel to be inspected; the number of defect detection modules is at least two, and each defect detection module corresponds to one scanning camera; and / or, the number of scans by the scanning camera is at least two, and the scanning field of view of the scanning camera is different in different scan processes; After all the scanning cameras have completed their scans, the detection control module performs image processing, including at least stitching, on all the image templates received from all the defect detection modules to obtain the low-resolution overall image of the display panel to be inspected.

6. The method as described in claim 5, characterized in that, The detection control module performs image processing on all the image templates, including at least stitching, to obtain the low-resolution overall image of the display panel to be detected, including: In a splicing direction that is parallel to the surface of the display panel to be detected and perpendicular to the running direction of the display panel to be detected, there is an overlapping area between two adjacent image templates; Based on the brightness information of the overlapping area between two adjacent image templates, the brightness of the two adjacent image templates is adjusted to the same brightness value.

7. The method as described in claim 6, characterized in that, Based on the brightness information of the overlapping region between two adjacent image templates, the brightness of the two adjacent image templates is adjusted to the same brightness value, including: One of the two adjacent image templates is used as the reference image template, and the other image template is used as the image template to be adjusted. Calculate the ratio of the mean gray value in the overlapping region of the adjusted image template to the mean gray value in the overlapping region of the reference image template; The mean ratio is used as a global gain coefficient when adjusting the brightness of the image template being adjusted, so that the brightness of two adjacent image templates is adjusted to the same brightness value.

8. The method as described in claim 6, characterized in that, The detection control module performs image processing, including at least stitching, on all the image templates to obtain the low-resolution overall image of the display panel to be detected, and further includes: During the process of stitching two adjacent image templates, the overlapping area of ​​one of the image templates is retained, while the overlapping area of ​​the other image template is removed. Based on the width value of the retained overlapping region in the splicing direction and the center line of the retained overlapping region parallel to the splicing direction, a gradual adjustment weight is determined to smoothly decrease from the center line of the retained overlapping region to the direction away from the center line of the retained overlapping region. The gradient adjustment weight is used as the adjustment weight for adjusting the grayscale value of each pixel in the retained overlapping region, and the grayscale value of each pixel in the retained overlapping region is adjusted.

9. The method as described in claim 8, characterized in that, The detection control module performs image processing, including at least stitching, on all the image templates to obtain the low-resolution overall image of the display panel to be detected, and further includes: Multiple image templates are sequentially stitched together from the first end of the stitching direction to the second end of the stitching direction, with two adjacent image templates stitched together to obtain the low-resolution overall image of the display panel to be detected; Specifically, when one of two adjacent image templates is used as the reference image template and the other image template is used as the image template to be adjusted, the image template closer to the first end of the splicing direction is used as the reference image template, and the image template closer to the second end of the splicing direction is used as the image template to be adjusted.

10. A high-resolution defect detection device, used for defect detection in display panels, characterized in that, The high-resolution inspection device includes a scanning camera, an inspection control module, and a defect detection module. The scanning camera is used to capture images frame by frame during the movement of the display panel to be inspected to obtain multiple high-resolution images. The defect detection module, under the control of the inspection control module, detects each frame of the high-resolution image to perform micro-defect detection on the display panel to be inspected. Furthermore, the high-resolution defect detection device is also used to perform the low-resolution defect detection method based on the high-resolution defect detection device as described in any one of claims 1-9.

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