Picture compression method in AOI (Automatic Optic Inspection) detection system and display panel defect detection system

A technology for displaying panel defects and compression methods, applied in image analysis, image communication, image data processing, etc., can solve problems such as resource consumption, image lossy compression, image data loss, etc., to reduce information volume, improve compression rate, The effect of reducing compression time

Active Publication Date: 2017-11-07

WUHAN JINGCE ELECTRONICS GRP CO LTD

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Problems solved by technology

However, the original image of the image detected by the display panel is relatively large. Although the use of lossless compression can reduce a part of the storage space, the compression efficiency is very slow, and the consumption of resources is very serious.

[0005] 2. Lossy compression of images

For example, image lossy compression using jpg format, although lossy compression can save a lot of storage space, and the efficiency is faster than lossl...

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Method used

In above-mentioned technical scheme, the reason that adopts pure white detection image as background is that pure white detection image defect is less, and generally does not exist the large-area brightness of Mura (referring to the phenomenon that display brightness is uneven, causes various traces) class uneven. The uneven brightness on the pure white test image is mainly due to the unevenness of the backlight and the vignetting effect of the camera, and these two factors are inherent in each test image. Using the pure white detection image as the background, and subtracting the pure white image from the rest of the images, this inherent inhomogeneity can be removed, thereby reducing the amount of information in the difference image.

[0025] Based on the same camera, the camera images under different display panel defect detection images have very similar characteristics, and the present invention proposes a high-efficiency lossless compression method for pictures. This method firstly takes the pure white detection image as...

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Abstract

The invention relates to a picture compression method in an AOI (Automatic Optic Inspection) detection system. The picture compression method comprises the following steps: step 1, arranging a display panel defect detection image group, determining a pure white detection image in the display panel defect detection image group as a first detection image, and sorting other detection images except the pure white detection image in the display panel defect detection image group in any order; step 2, performing a difference value subtraction operation on pixel values of other images except the pure white detection image and a pure black detection image in the display panel defect detection image group and a pixel value of the first detection image orderly, and obtaining a plurality of corresponding foreground images; step 3, removing a negative value of the pixel value of each foreground image and obtaining each corrected foreground image; and step 4, respectively performing image lossless compression on each corrected foreground image, and directly performing image lossless compression on the pure black detection image and the pure white detection image. The picture compression method in the AOI detection system provided by the invention can guarantee the compression ratio and shorten the compression time.

Application Domain

Image analysisTelevision systems +1

Technology Topic

Surface plateLossless compression +5

Image

Examples

Experimental program(1)

Example Embodiment

[0023] The present invention will be further described in detail below in conjunction with specific embodiments:

[0024] For display panel AOI defect detection, it is generally necessary to take multiple display panel defect detection images, such as figure 2 As shown, in the process of taking each display panel defect detection image, the relative position of the camera and the display panel does not change. Therefore, the difference between the different display panel defect detection images taken by each camera is relatively small. These differences are often caused by the defects of the display panel itself. Using the pure white detection image as the background, and subtracting the pure white image from the rest of the image, a large amount of repetitive information can be removed and key effective information is retained.

[0025] Based on the same camera, images taken by cameras under different display panel defect detection images have very similar characteristics. The present invention proposes an efficient image lossless compression method. This method first takes the pure white detection image as the benchmark, and subtracts the pixel value of the pure white detection image before compressing each image to obtain the foreground image (difference image). In order to avoid the negative value of the foreground image, each foreground image The pixel value is 128 shifted. After preprocessing, the background information in the image is gone, and what is left is the foreground information with less information. Then, the image of the processed foreground information is losslessly compressed. Because the image information at this time is relatively simple, use The lossless compression algorithm can be processed efficiently and quickly. The specific method of the present invention includes the following steps:

[0026] Step 1: Arrange the display panel defect detection image group, determine the pure white detection image in the display panel defect detection image group as the first detection image, and set the display panel defect detection image group except the pure white detection image Other inspection images are sorted in any order to obtain the display panel defect inspection image sequence, such as figure 2 Shown

[0027] Step 2: The pixel values of the remaining images except the pure white inspection image and the pure black inspection image in the display panel defect inspection image sequence are sequentially subtracted from the pixel values of the first inspection image to obtain multiple corresponding foregrounds image;

[0028] Step 3: Remove the negative value of the pixel value of each foreground image to obtain each corrected foreground image;

[0029] Step 4: Perform image lossless compression on each corrected foreground image and save it, at the same time, directly perform image lossless compression on the pure black detection image and pure white detection image and save it;

[0030] Step 5: Perform secondary compression (using a zip compression method) on all corrected foreground images after lossless compression in step 4 and the pure black detection images and pure white detection images after lossless compression to form a defect detection image compression package.

[0031] In the above technical solution, the display panel defect detection image group includes a full white screen (L255), a full red screen (R255), a full green screen (G255), a full blue screen (B255), a full black screen (L0), RGB The value (red, green, and blue) is a grayscale screen (L127) with 127 values, a grayscale screen with RGB values of 48 (L48), a grayscale screen with RGB values of X, and the range of X is 0 ~255.

[0032] In step 3 of the above technical solution, an operation of adding a preset pixel value is performed on the pixels of each foreground image, thereby removing the negative value of the pixel value of each foreground image. If there is a negative number in the pixel value of the foreground image, when performing lossless compression, the data storage method must use integer (4 bytes), which consumes resources; if there is no negative number in the pixel value of the foreground image, when performing lossless compression , Data storage only needs to use uchar type (1 byte), which can significantly improve the efficiency of subsequent lossless compression.

[0033] In step 3 of the above technical solution, the preset pixel value added to each pixel of the foreground image is equal. The pixel of each foreground image plus the same preset pixel value is conducive to the decoding and restoration of the later compressed image.

[0034] The preset pixel value is preferably 128. The preset pixel value can ensure that the pixel values of all foreground images become positive values.

[0035] In the above technical solution, since the pure black detection image itself has less information, except for some bright spots, the rest of the pixel values are all 0, so the lossless compression processing can be directly performed.

[0036] In the above technical solution, the reason for using the pure white detection image as the background is that the pure white detection image has fewer defects and generally does not have large-area uneven brightness such as Mura (referring to the phenomenon of uneven display brightness, which causes various traces). The brightness unevenness on the pure white detection image is mainly caused by the unevenness of the backlight and the vignetting effect of the camera, and these two factors are inherently existent in each detection image. Using the pure white detection image as the background, and subtracting the pure white image from the remaining images, this inherent inhomogeneity can be removed, thereby reducing the amount of information in the difference image.

[0037] In the subsequent use of the present invention, an image restoration operation is required, and only the reverse process of the above operation is required. First decompress the defect detection image compression package, and then perform lossless compression decoding, subtract 128 pixel values from the pixel value of the decoded image, and finally add the pixel value of the pure white detection image to restore it.

[0038] The following selects the L48 grayscale picture and combines the drawings to illustrate the effect of the present invention:

[0039] The invention will be as Figure 4 with 5 The pixel value of the L48 grayscale picture shown is subtracted as image 3 The pixel value of the pure white detection image as shown, and then add 128 pixel values to the difference to get Image 6 with 7 For the corrected foreground image shown, the corrected foreground image is finally compressed and saved without loss. by Image 6 with 7 It can be clearly seen that the local details of the corrected foreground image are greatly reduced compared with the L48 grayscale image before the above process is not processed, that is, the amount of information of the image is greatly reduced; the specific effect of the L48 grayscale image compressed by the solution of the present invention is shown in Table 1. .

[0040] Table 1: Comparison table of effects of conventional compression scheme and compression scheme of the present invention

[0041]

[0042] A display panel defect detection system based on the above image compression method, such as figure 1 As shown, it includes an image capture storage server and a detection server. The image capture storage server is used to obtain a display panel defect detection image group from an industrial camera, and transmit the acquired display panel defect detection image group to the detection server; the detection server Used to perform display panel defect detection based on the acquired display panel defect detection image group, and output the detection result;

[0043] The image capture and storage server is also used to perform image compression processing on the detected defect detection image of the display panel using the method described in step 1 to step 4, and save the compressed image on the local hard disk.

[0044] A computer-readable storage medium that stores a computer program, and when the computer program is executed by a processor, the steps of the method described in steps 1 to 4 are realized.

[0045] In step 4 of the above technical solution, the image lossless compression method can adopt the image lossless compression method based on static and dynamic Huffman coding algorithm, the image lossless compression method based on arithmetic coding algorithm, and the image based on LZW (lanpel-ziv-velch) coding. Image lossless compression method and its improved algorithm, image lossless compression method based on run length coding and improved adaptive run length coding algorithm, or image lossless compression method based on Fino Shannon coding algorithm.

[0046] The content not described in detail in this specification belongs to the prior art known to those skilled in the art.

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Picture compression method in AOI (Automatic Optic Inspection) detection system and display panel defect detection system

AI-Extracted Technical Summary

Problems solved by technology

Method used

Abstract

Image

Examples

Example Embodiment

PUM

Description & Claims & Application Information

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