CN118603505A - A LCD defect detection method based on uniformity correction - Google Patents

Abstract

The present invention discloses an LCD defect detection method based on uniformity correction, comprising: taking a good display panel glass and placing it on a test fixture to light it up, and obtaining a first white screen image; processing the first white screen image and obtaining a first gain coefficient of each pixel of the first AA area image of the first white screen image; placing the display panel glass to be tested on the test fixture to light it up, and obtaining a second white screen image; multiplying the grayscale value of each pixel of the second AA area image of the second white screen image by the first gain coefficient to perform uniformity correction on the second white screen image, and obtaining a third white screen image; and performing display function defect detection on the third white screen image. The implementation of the present invention effectively eliminates display anomalies caused by scratches and dirt on the backlight of the fixture itself and dark edges, highlights the contrast between the display defects of the display panel glass to be tested and the background, and reduces the misjudgment rate of display function defects.

Description

A LCD defect detection method based on uniformity correction

Technical Field

The present invention relates to the technical field of display screen defect detection, and in particular to an LCD defect detection method based on uniformity correction.

Background Art

TFT-LCD (Thin Film Field Effect Transistor Liquid Crystal Display) is a photoelectric display device that realizes display by controlling the orientation of liquid crystal molecules with anisotropy of refractive index to change the transmittance through the liquid crystal screen. Thin film transistors (TFT) play a switching role in it. In recent years, it has become a new generation of mainstream displays and is widely used in display fields such as laptops, desktop monitors, liquid crystal televisions, and mobile display terminals. LCD consists of polarizers, filters, liquid crystals, drive circuits, and backlight panels. During the processing and manufacturing of LCD devices, dozens of processes will be required in the array, cell, and module stages. During the processing and manufacturing of the display screen, various defects may occur due to the characteristics of raw materials and production processes, such as light leakage caused by the loose fit between the organic light-emitting layer of the liquid crystal layer of the LCD screen and the frame, mura (uneven display) caused by various manufacturing processes, bubbles, scratches, and dirt on the screen substrate or filter, and bad points (bright spots and dark spots) caused by the failure of pixels to work properly. At the same time, there may also be defects such as color deviation caused by the deflection problem of the liquid crystal on the LCD screen.

Therefore, it is necessary to perform defect detection on the LCD display function. However, when the detection equipment performs LCD (display without its own light source) lighting function defect inspection, due to factors such as test fixture shading design and production deviation, uneven backlight brightness, dirty backlight, camera dark corners, etc., when the CCD takes pictures of the LCD screen, the image brightness is uneven and the middle is bright and the surroundings are dark. For some minor low-contrast display defects (such as mura, dark scratches and other display defects), this undesirable phenomenon is easy to cause missed judgments, increasing the misjudgment rate of the inspection equipment.

Summary of the invention

When testing the display function defects of existing LCDs, due to factors such as the test fixture's own shading design and manufacturing deviations, uneven backlight brightness, dirty backlight, and camera vignetting, the LCD screen image captured by the CCD camera shows problems such as uneven brightness and bright in the middle and dark around, which makes it easy for some minor low-contrast display defects (such as mura, dark scratches, and other display defects) to be missed.

To solve the above problems, a LCD defect detection method based on uniformity correction is proposed. By obtaining the gain coefficient of the AA area of the qualified display panel glass and multiplying the gain coefficient with the grayscale value of the pixel in the AA area of the display panel glass to be tested, the display anomaly caused by scratches and dirt on the backlight of the fixture itself and dark edges is eliminated, the contrast between the display defects of the display panel glass to be tested and the background is highlighted, and the misjudgment rate of display function defects is reduced.

In a first aspect, a method for detecting LCD defects based on uniformity correction includes:

Step 100: Take a good display panel glass and place it on the test fixture to light it up, and obtain a first white screen image;

Step 200: Process the first white screen image and obtain a first gain coefficient of each pixel of a first AA area image of the first white screen image;

Step 300: placing the display panel glass to be tested on the test fixture, lighting it, and acquiring a second white screen image;

Step 400: multiply the grayscale value of each pixel of the second AA area image of the second white screen image by the first gain coefficient to perform uniformity correction on the second white screen image to obtain a third white screen image;

Step 500: Perform display function defect detection on the third white screen image.

In conjunction with the LCD defect detection method based on uniformity correction according to the first aspect of the present invention, in a first possible implementation manner, step 100 includes:

Step 110: In a dark field environment, fix the lighting fixture and the CCD camera in relative position;

Step 120: debug the CCD camera to make it have clear imaging.

In combination with the first possible implementation manner of the first aspect of the present invention, in a second possible implementation manner, step 100 further includes:

Step 130, setting the gray value of the brightest image of the CCD camera;

Step 140: Use the CCD camera to obtain the first white screen image of the good display panel glass.

In combination with the LCD defect detection method based on uniformity correction according to the first aspect of the present invention, in a third possible implementation manner, step 200 includes:

Step 210: Use the Otsu algorithm to perform threshold segmentation on the first white screen image to obtain a first AA area image;

Step 220: Perform median filtering to reduce noise on the first AA region image to make the first AA region image smooth.

In combination with the third possible implementation manner of the first aspect of the present invention, in a fourth possible implementation manner, step 200 further includes:

Step 230, calculating the average gray value of the first AA area image;

Step 240: Divide the average grayscale value by the grayscale value of each pixel to obtain the first gain coefficient.

In combination with the LCD defect detection method based on uniformity correction according to the first aspect of the present invention, in a fifth possible implementation manner, step 400 includes:

Step 410: Perform threshold segmentation on the second white screen image using the Otsu algorithm to obtain a second AA area image;

Step 420: Perform median filtering to reduce noise on the second AA region image to make the second AA region image smooth;

Step 430: multiply the grayscale value of each pixel of the second AA region image by the first gain coefficient to enhance the contrast between the glass defect of the display panel to be tested and the background and eliminate the display anomaly caused by the deviation of the fixture itself.

In a second aspect, a method for detecting LCD defects based on uniformity correction includes:

Step 600: Take a piece of good display panel glass, place it on the test fixture, light it up, and obtain a first color screen image, process the first color screen image and obtain a gain coefficient of each pixel of each channel AA area image of the first color screen image;

Step 700: placing the display panel glass to be tested on the fixture, lighting it, and acquiring a second color screen image;

Step 800: multiply the gray value of each pixel of the AA region image of each channel of the second color screen image by the gain coefficient of the corresponding channel image to perform uniformity correction on the second color screen image to obtain a third color screen image;

Step 900: Perform display function defect detection on the third color screen image.

In conjunction with the LCD defect detection method based on uniformity correction according to the second aspect of the present invention, in a first possible implementation manner, step 600 includes:

Step 610: decompose the first color screen image into a first R channel screen image, a first G channel screen image, and a first B channel screen image; perform threshold segmentation on the first R channel screen image, the first G channel screen image, and the first B channel screen image using an Otsu algorithm to obtain a first R channel AA region image, a first G channel AA region image, and a first B channel AA region image;

Step 620: Perform median filtering to reduce noise on the first R channel AA region image, the first G channel AA region image, and the first B channel AA region image to make the first R channel AA region image, the first G channel AA region image, and the first B channel AA region image smooth.

In combination with the first possible implementation manner of the second aspect of the present invention, in a second possible implementation manner, step 600 further includes:

Step 630, respectively calculating the first R channel average gray value, the first G channel average gray value, and the first B channel average gray value of the first R channel AA region image, the first G channel AA region image, and the first B channel AA region image;

Step 640: Divide the first R channel average grayscale value, the first G channel average grayscale value, and the first B channel average grayscale value by the grayscale value of each pixel to obtain a first R channel gain coefficient, a first G channel gain coefficient, and a first B channel gain coefficient.

In combination with the LCD defect detection method based on uniformity correction according to the second aspect of the present invention, in a third possible implementation manner, step 800 includes:

Step 810: decompose the second color screen image into a second R channel screen image, a second G channel screen image, and a second B channel screen image; perform threshold segmentation on the second R channel screen image, the second G channel screen image, and the second B channel screen image using an Otsu algorithm to obtain a second R channel AA region image, a second G channel AA region image, and a second B channel AA region image;

Step 820: Multiply the grayscale values of the pixels of the second R channel AA area image, the second G channel AA area image, and the second B channel AA area image by the first R channel gain coefficient, the first G channel gain coefficient, and the first B channel gain coefficient, respectively, to obtain a third R channel AA area image, a third G channel AA area image, and a third B channel AA area image;

Step 830: Merge the third R channel AA area image, the third G channel AA area image, and the third B channel AA area image to obtain the third color screen image.

The LCD defect detection method based on uniformity correction described in the present invention is implemented to obtain the gain coefficient of the AA area of the good display panel glass, and multiply the gain coefficient by the grayscale value of the pixel in the AA area of the display panel glass to be tested, thereby eliminating the display anomaly caused by scratches and dirt on the backlight of the fixture itself and dark edges, highlighting the contrast between the display defects of the display panel glass to be tested and the background, and reducing the misjudgment rate of display function defects.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

FIG1 is a schematic diagram of display abnormality caused by a test fixture in the present invention;

FIG2 is a schematic diagram of a white screen image before the display panel glass to be tested is calibrated in the present invention;

FIG. 3 is a schematic diagram of a white screen image of the display panel glass to be tested before calibration in the present invention.

DETAILED DESCRIPTION

The following will be combined with the accompanying drawings in the invention to clearly and completely describe the technical solutions in the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in the present invention, other embodiments obtained by ordinary technicians in this field without creative work are all within the scope of protection of the present invention.

Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those generally understood by those skilled in the art of the present invention. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and/or" used herein includes any and all combinations of one or more related listed items.

It should be noted that when an element is referred to as being "fixed to" or "disposed on" another element, it can be directly on the other element or indirectly on the other element. When an element is referred to as being "connected to" another element, it can be directly connected to the other element or indirectly connected to the other element.

It should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating the orientation or position relationship, are based on the orientation or position relationship shown in the drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present application.

In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of this application, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

When the existing LCD is being tested for display function defects 20, due to the test fixture's own shading design and manufacturing deviations, uneven backlight brightness, dirty backlight, camera vignetting and other factors, the LCD screen image obtained by the CCD camera shows problems of uneven brightness display and bright in the middle and dark around, making some slight low-contrast display defects (such as mura, dark scratches and other display defects) easily missed.

To solve the above problems, a LCD defect detection method based on uniformity correction is proposed.

In a first aspect, a method for detecting LCD defects based on uniformity correction includes:

Step 100: Take a piece of good display panel glass, place it on a test fixture, light it up, and obtain a first white screen image.

Preferably, step 100 includes: step 110, fixing the relative position of the lighting fixture and the CCD camera in a dark field environment; step 120, debugging the CCD camera to make its imaging clear.

Preferably, step 100 further includes: step 130, setting the gray value of the brightest image of the CCD camera; step 140, acquiring a first white screen image of a good display panel glass by using the CCD camera.

In a dark environment, place and fix the lighting test fixture, set up the CCD camera on the test fixture, and keep the relative position of the CCD camera and the test fixture unchanged. Place the display panel glass (LCD) with good display function on the lighting test fixture, display a white screen (or other monochrome screen), adjust the aperture and focal length of the CCD camera or the backlight of the lighting test fixture to make the CCD camera image clear, and set the brightest grayscale value of the CCD camera image to about 180.

The dotted box represents the display abnormality 10 phenomenon in which the white screen is dark around and bright in the middle due to dirt and scratches on the backlight itself, as well as uneven brightness and camera vignetting, as shown in FIG1 . FIG1 is a schematic diagram of the display abnormality 10 caused by the test fixture in the present invention.

Step 200: Process a first white screen image and obtain a first gain coefficient of each pixel in a first AA region image of the first white screen image.

Preferably, step 200 includes: step 210, performing threshold segmentation on the first white screen image using the Otsu algorithm to obtain a first AA region image; step 220, performing median filtering to reduce noise on the first AA region image to make the first AA region image smooth.

Preferably, step 200 further includes: step 230, calculating the average gray value of the first AA region image; step 240, dividing the average gray value by the gray value of each pixel to obtain a first gain coefficient.

The CCD camera acquires the first white screen image, and the AA area (Active Area) of the LCD in the first white screen image is segmented out through the Otsu algorithm (maximum inter-class variance method) to obtain the AAReg area. The median filter is used to reduce noise in the area to smooth the image, and the average grayscale value GrayMean of the area is obtained. The average grayscale value GrayMean is then divided by the grayscale value of each pixel in the area to obtain the real number type gain coefficient Gain_K of each pixel (each pixel corresponds to a gain coefficient), which is also the screen uniformity correction coefficient.

Step 300: Place the display panel glass to be tested on a test fixture and light it up, and obtain a second white screen image.

Step 400: multiply the grayscale value of each pixel of the second AA region image of the second white screen image by the first gain coefficient to perform uniformity correction on the second white screen image to obtain a third white screen image.

Preferably, as shown in Figures 2 and 3, Figure 2 is a schematic diagram of a white screen image before the display panel glass to be tested is corrected in the present invention, and Figure 3 is a schematic diagram of a white screen image before the display panel glass to be tested is corrected in the present invention; step 400 includes: step 410, using the Otsu algorithm to perform threshold segmentation on the second white screen image to obtain a second AA area image; step 420, performing median filtering and noise reduction on the second AA area image to make the second AA area image smooth; step 430, multiplying the grayscale value of each pixel of the second AA area image by the first gain coefficient to enhance the contrast between the display function defect 20 of the display panel glass to be tested and the background, and eliminate the display abnormality 10 caused by the deviation of the fixture itself.

During the test, the display panel glass with display defects to be tested is placed on the test fixture and lit, the display screen is white, and the CCD camera takes pictures. The image of the AA area is intercepted, and each pixel of the image is multiplied by each corresponding gain coefficient Gain_K obtained above to obtain a uniformly corrected image, highlighting the contrast between the display function defect 20 of the display panel glass to be tested and the background. After correction, the contrast of the display function defect 20 of the display panel glass to be tested is enhanced, the scratches and dirt on the backlight of the test fixture itself are corrected and disappeared, and the display abnormality 10 at the dark edge of the AA area is also corrected uniformly.

Step 500: Detect the display function defect 20 on the third white screen image. By obtaining the gain coefficient of the AA area of the good display panel glass and multiplying the gain coefficient with the grayscale value of the pixel in the AA area of the display panel glass to be tested, the display abnormality 10 caused by the scratches and dirt on the backlight of the fixture itself and the dark edge is eliminated, the contrast between the display defect of the display panel glass to be tested and the background is highlighted, and the misjudgment rate of the display function defect 20 is reduced.

In a second aspect, a method for detecting LCD defects based on uniformity correction includes:

Step 600: Take a good display panel glass, place it on the test fixture, light it up, and obtain a first color screen image. Process the first color screen image and obtain the gain coefficient of each pixel of each channel AA area image of the first color screen image.

Preferably, step 600 includes: step 610, decomposing the first color screen image into a first R channel screen image, a first G channel screen image, and a first B channel screen image, and using the Otsu algorithm to perform threshold segmentation on the first R channel screen image, the first G channel screen image, and the first B channel screen image to obtain the first R channel AA area image, the first G channel AA area image, and the first B channel AA area image; step 620, performing median filtering to reduce noise on the first R channel AA area image, the first G channel AA area image, and the first B channel AA area image to make the first R channel AA area image, the first G channel AA area image, and the first B channel AA area image smooth.

Preferably, step 600 also includes: step 630, respectively calculating the first R channel average grayscale value, the first G channel average grayscale value, and the first B channel average grayscale value of the first R channel AA area image, the first G channel AA area image, and the first B channel AA area image; step 640, respectively dividing the first R channel average grayscale value, the first G channel average grayscale value, and the first B channel average grayscale value by the grayscale value of each pixel to obtain the first R channel gain coefficient (Gain_K_R), the first G channel gain coefficient (Gain_K_G), and the first B channel gain coefficient (Gain_K_B).

If the acquired image is an RGB three-channel color image, it is necessary to decompose the color image into three single-channel images of red, green and blue, calculate the three average grayscale values of the three single-channel images in the AA area, and then calculate the gain coefficients Gain_K_R, Gain_K_G, Gain_K_B).

Step 700: Place the display panel glass to be tested on a fixture, light it up, and obtain a second color screen image;

Step 800: multiply the grayscale value of each pixel of the AA region image of each channel of the second color image by the gain coefficient of the corresponding channel image to perform uniformity correction on the second color image to obtain a third color image.

Preferably, step 800 includes: step 810, decomposing the second color screen image into a second R channel screen image, a second G channel screen image, and a second B channel screen image, and performing threshold segmentation on the second R channel screen image, the second G channel screen image, and the second B channel screen image using the Otsu algorithm to obtain a second R channel AA area image, a second G channel AA area image, and a second B channel AA area image; step 820, multiplying the grayscale values of the pixels of the second R channel AA area image, the second G channel AA area image, and the second B channel AA area image with the first R channel gain coefficient (Gain_K_R), the first G channel gain coefficient (Gain_K_G), and the first B channel gain coefficient (Gain_K_B), respectively, to obtain a third R channel AA area image, a third G channel AA area image, and a third B channel AA area image; step 830, merging the third R channel AA area image, the third G channel AA area image, and the third B channel AA area image to obtain a third color screen image.

Each pixel in the AA area of each single-channel image is multiplied by the corresponding gain coefficient, and the three images after the multiplication are combined into a three-channel color image.

Step 900: Detect the display function defect 20 on the third color screen image.

The present invention implements an LCD defect detection method based on uniformity correction, which obtains the gain coefficient of the AA area of the good display panel glass and multiplies the gain coefficient by the grayscale value of the pixel in the AA area of the display panel glass to be tested, thereby eliminating the display anomaly 10 caused by scratches and dirt on the backlight of the fixture itself and dark edges, highlighting the contrast between the display defect of the display panel glass to be tested and the background, and reducing the misjudgment rate of display function defects 20.

The above are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims (10)

1. A method for LCD defect detection based on uniformity correction, comprising: Step 100: Take a good display panel glass and place it on the test fixture to light it up, and obtain a first white screen image; Step 200: Process the first white screen image and obtain a first gain coefficient of each pixel of a first AA area image of the first white screen image; Step 300: placing the display panel glass to be tested on the test fixture, lighting it, and acquiring a second white screen image; Step 400: multiply the grayscale value of each pixel of the second AA area image of the second white screen image by the first gain coefficient to perform uniformity correction on the second white screen image to obtain a third white screen image; Step 500: Perform display function defect detection on the third white screen image. 2. The LCD defect detection method based on uniformity correction according to claim 1, wherein step 100 comprises: Step 110: In a dark field environment, fix the lighting fixture and the CCD camera in relative position; Step 120: debug the CCD camera to make it have clear imaging. 3. The LCD defect detection method based on uniformity correction according to claim 2, wherein step 100 further comprises: Step 130, setting the gray value of the brightest image of the CCD camera; Step 140: Use the CCD camera to obtain the first white screen image of the good display panel glass. 4. The LCD defect detection method based on uniformity correction according to claim 1, wherein step 200 comprises: Step 210: Use the Otsu algorithm to perform threshold segmentation on the first white screen image to obtain a first AA area image; Step 220: Perform median filtering to reduce noise on the first AA region image to make the first AA region image smooth. 5. The LCD defect detection method based on uniformity correction according to claim 4, characterized in that the step 200 further comprises: Step 230, calculating the average gray value of the first AA area image; Step 240: Divide the average grayscale value by the grayscale value of each pixel to obtain the first gain coefficient. 6. The LCD defect detection method based on uniformity correction according to claim 1, wherein step 400 comprises: Step 410: Perform threshold segmentation on the second white screen image using the Otsu algorithm to obtain a second AA area image; Step 420: Perform median filtering to reduce noise on the second AA region image to make the second AA region image smooth; Step 430: multiply the grayscale value of each pixel of the second AA region image by the first gain coefficient to enhance the contrast between the glass defect of the display panel to be tested and the background and eliminate the display anomaly caused by the deviation of the fixture itself. 7. A method for LCD defect detection based on uniformity correction, comprising: Step 600: Take a piece of good display panel glass, place it on the test fixture, light it up, and obtain a first color screen image, process the first color screen image and obtain a gain coefficient of each pixel of each channel AA area image of the first color screen image; Step 700: placing the display panel glass to be tested on the fixture, lighting it, and acquiring a second color screen image; Step 800: multiply the gray value of each pixel of the AA region image of each channel of the second color screen image by the gain coefficient of the corresponding channel image to perform uniformity correction on the second color screen image to obtain a third color screen image; Step 900: Perform display function defect detection on the third color screen image. 8. The LCD defect detection method based on uniformity correction according to claim 7, wherein step 600 comprises: Step 610: decompose the first color screen image into a first R channel screen image, a first G channel screen image, and a first B channel screen image; perform threshold segmentation on the first R channel screen image, the first G channel screen image, and the first B channel screen image using an Otsu algorithm to obtain a first R channel AA region image, a first G channel AA region image, and a first B channel AA region image; Step 620: Perform median filtering to reduce noise on the first R channel AA region image, the first G channel AA region image, and the first B channel AA region image to make the first R channel AA region image, the first G channel AA region image, and the first B channel AA region image smooth. 9. The LCD defect detection method based on uniformity correction according to claim 8, wherein step 600 further comprises: Step 630, respectively calculating the first R channel average gray value, the first G channel average gray value, and the first B channel average gray value of the first R channel AA region image, the first G channel AA region image, and the first B channel AA region image; Step 640: Divide the first R channel average grayscale value, the first G channel average grayscale value, and the first B channel average grayscale value by the grayscale value of each pixel to obtain a first R channel gain coefficient, a first G channel gain coefficient, and a first B channel gain coefficient. 10. The LCD defect detection method based on uniformity correction according to claim 7, wherein step 800 comprises: Step 810: decompose the second color screen image into a second R channel screen image, a second G channel screen image, and a second B channel screen image; perform threshold segmentation on the second R channel screen image, the second G channel screen image, and the second B channel screen image using an Otsu algorithm to obtain a second R channel AA region image, a second G channel AA region image, and a second B channel AA region image; Step 820: Multiply the grayscale values of the pixels of the second R channel AA area image, the second G channel AA area image, and the second B channel AA area image by the first R channel gain coefficient, the first G channel gain coefficient, and the first B channel gain coefficient, respectively, to obtain a third R channel AA area image, a third G channel AA area image, and a third B channel AA area image; Step 830: Merge the third R channel AA area image, the third G channel AA area image, and the third B channel AA area image to obtain the third color screen image.