WO2020098181A1 - 一种液晶面板缺陷检测方法及其系统 - Google Patents

一种液晶面板缺陷检测方法及其系统 Download PDF

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Publication number
WO2020098181A1
WO2020098181A1 PCT/CN2019/077042 CN2019077042W WO2020098181A1 WO 2020098181 A1 WO2020098181 A1 WO 2020098181A1 CN 2019077042 W CN2019077042 W CN 2019077042W WO 2020098181 A1 WO2020098181 A1 WO 2020098181A1
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liquid crystal
crystal panel
area
detected
image
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PCT/CN2019/077042
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English (en)
French (fr)
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张沛
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深圳市华星光电半导体显示技术有限公司
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Publication of WO2020098181A1 publication Critical patent/WO2020098181A1/zh

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/95—Investigating the presence of flaws or contamination characterised by the material or shape of the object to be examined
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
    • G01N2021/8854—Grading and classifying of flaws
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
    • G01N2021/8887—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges based on image processing techniques
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/95—Investigating the presence of flaws or contamination characterised by the material or shape of the object to be examined
    • G01N2021/9513—Liquid crystal panels

Definitions

  • the invention relates to the technical field of liquid crystal panel defect detection, in particular to a liquid crystal panel defect detection method and system.
  • the commonly used detection method is to use the API (Application Program Interface) application system for detection.
  • the method of searching for the AA (Active Area) display area in the liquid crystal display panel is to sample the white screen and the camera is overexposed After combining the software to distinguish the seal area and the AA display area through the gray-scale difference, manually inspect the defects in each area.
  • the detection method requires the purchase of professional burr inspection machines and product delivery equipment, which increases production costs to a certain extent. Furthermore, it will eventually require manual inspection, and the accuracy of manual inspection is uncontrollable, the reliability is relatively low, and the inspection process cycle is long.
  • the present invention provides a liquid crystal panel defect detection method and system, which can automatically perform overexposure photography and image contrast detection, and also includes an API detection device, which can realize all functions of the burr inspection machine, so that it can pass only Adding a small number of production cycles can realize the LCD panel defect detection process, effectively reducing the overall production cycle, reducing equipment costs and labor costs, and the detection accuracy is more controllable, thereby improving the detection reliability.
  • An embodiment of the present invention provides a defect detection method for a liquid crystal panel, the detection method includes:
  • Reference image creation step collect images of each area of the reference LCD panel, perform geometric correction and filtering on the images, as a comparison reference image, and use software to distinguish the collected images of each area through gray-scale difference Backlight (BL) area and the edge boundary of the LCD panel area, record the gray scale value of each area pixel, and define the gray scale value range of each area;
  • BL gray-scale difference Backlight
  • Step of making the image of the liquid crystal panel to be detected collecting the image of the liquid crystal panel to be detected in an overexposure state, and obtaining the gray scale value range of each area;
  • Each area in turn knows its backlight area and LCD panel area;
  • Step of identifying defects analyzing the straightness of the four sides of the image of the detected liquid crystal panel area and comparing with the corresponding position of the reference image. When the difference between the two exceeds a predetermined value, the Detecting defects in the liquid crystal panel, wherein the predetermined value is in the range of 0.1 to 0.5 mm.
  • the detected defects include defects with abnormal cutting accuracy, which is to compare the edge boundary of the image of the liquid crystal panel to be inspected with the reference image, and to calculate the respective sides of the panel in the image of the liquid crystal panel to be inspected and the reference image
  • the predetermined value is in the range of 0.15 ⁇ 0.5mm.
  • the detected defects include cut convex edge convex corner defects, which are used to calculate the distance between the liquid crystal panel image to be inspected and the respective sides of the corresponding panel in the reference image, when any side of the liquid crystal panel to be inspected protrudes
  • the distance value of the corresponding side of the comparison reference panel area is greater than the predetermined value, it belongs to a convex edge convex corner defect; wherein the predetermined value is in the range of 0.1-0.25 mm.
  • the detected defects include fragmentation defects, which is to calculate the distance between the liquid crystal panel image to be inspected and the corresponding sides of the panel in the comparison reference image, when any side of the liquid crystal panel area to be inspected is indented to the comparison reference When the distance value of the corresponding side of the panel area is greater than the predetermined value, it is a fragment defect; wherein the predetermined value is in the range of 0.1-0.25 mm.
  • the defect detection method of the liquid crystal panel further includes steps:
  • the processing unit calculates the number of difference pixels of the liquid crystal panel to be detected and the comparison reference panel. When the number of difference pixels is greater than 5, it is the number of defective pixels of the liquid crystal panel to be detected. Detect the size of the number of defective pixels of the liquid crystal panel to divide the defect level.
  • step S5 dividing the defect level according to the size of the number of defective pixels of the liquid crystal panel to be detected specifically includes: according to step S4, the abnormal cutting accuracy defect, the convex edge defect, and the fragment defect are statistically calculated
  • the number of defective pixels of the liquid crystal panel to be detected; or, the number of defective pixels of the liquid crystal panel to be detected is calculated according to the sum of the abnormal cutting accuracy defects, ridge and corner defects, and fragment defects described in step S4; or, according to the steps In S4, the number of defective pixels of the liquid crystal panel to be detected is calculated by weighted summing of abnormal cutting accuracy defects, convex edge convex corner defects, and fragment defects.
  • the method of calculating the types of defects can be used to calculate the statistics of different types of defects.
  • the method of summing the types of defects can count the size of the total defect area for quick identification.
  • the weighted sum of the types of defects can be used to control the impact according to different weights. Degree to set.
  • the method of acquiring the image of the liquid crystal panel to be detected in an overexposure state is to remove the polarizing effect on the photographing lens to make it appear in the overexposure state, so as to obtain the image of the liquid crystal panel to be detected.
  • the way to remove the polarizing effect on the camera lens is to drive the polarizer on the camera lens to be removed by a motor, or to drive the upper polarizer or the lower polarizer of the polarizer on the camera lens through a motor
  • the plate is rotated 90 degrees, so that the polarization directions of the upper polarizer and the lower polarizer are parallel without polarizing effect.
  • One embodiment of the present invention provides a defect detection system for a liquid crystal panel, including an API detection device, a camera lens, a motor, a backlight area, and a support structure.
  • the API detection device is used to process the received data and output the processing result.
  • the camera lens is used to capture and obtain a comparison reference image and an image of a liquid crystal panel to be detected and send the image data to the API detection device.
  • the camera lens includes a polarizer (POL) and a photosensitive element; the motor It is used to move the polarizer on the camera lens; the backlight device is used to provide a backlight source when shooting, the center of the backlight area defined by the backlight device is opposite to the camera lens; the support structure is located in the backlight device Around the surrounding area, the area enclosed by the support structure is opposite to the backlight area defined by the backlight device.
  • POL polarizer
  • photosensitive element the motor It is used to move the polarizer on the camera lens
  • the backlight device is used to provide a backlight source when shooting, the center of the backlight area defined by the backlight device is opposite to the camera lens
  • the support structure is located in the backlight device Around the surrounding area, the area enclosed by the support structure is opposite to the backlight area defined by the backlight device.
  • the use of motor control can set the timing of rotating the polarizer according to the cycle time of the beat, which is more intelligent and automated.
  • the relative setting of the area enclosed by the support structure and the backlight area can prevent the camera lens from being affected by the support structure, complete the shooting of the backlight area, and can be better identified and analyzed.
  • the backlight provided in the backlight area during the shooting can illuminate the edge of the liquid crystal panel to be detected, so that the edge of the liquid crystal panel to be detected can be clearer when the image of the liquid crystal panel to be detected is overexposed.
  • the present invention provides a method and device for detecting defects of a liquid crystal panel, which can automatically perform overexposure photography and image contrast detection, and also includes an API detection device, which can realize all functions of the burr inspection machine, so that it can
  • the liquid crystal panel defect detection process can be realized by only adding a small number of production cycles, effectively reducing the overall production cycle, reducing equipment costs and labor costs, and the detection accuracy is more controllable, thereby improving the detection reliability.
  • FIG. 1 is a flowchart of a method for detecting defects of a liquid crystal panel according to a first embodiment of the invention
  • FIG. 2 is a flowchart of a method for detecting defects of a liquid crystal panel according to a second embodiment of the invention
  • FIG. 3 is a schematic diagram comparing the image of the liquid crystal panel to be detected and the reference image according to the third embodiment of the present invention
  • FIG. 4 is a front view of a liquid crystal panel defect detection system according to a fourth embodiment of the invention.
  • FIG. 5 is a top view of a liquid crystal panel defect detection system according to a fifth embodiment of the invention.
  • Backlight device 21, sealed area, 22.
  • An embodiment of the present invention provides a method for detecting defects of a liquid crystal panel. Please refer to FIG. 1 and FIG. 3, the detection method includes:
  • Reference image creation step collect images of each area of the reference LCD panel, perform geometric correction and filtering on the images, as a comparison reference image, and use software to distinguish the collected images of each area through gray-scale difference
  • the edge boundaries of the backlight area 1 and the liquid crystal panel area 2 record the grayscale values of pixels in each area to define the grayscale value range of each area.
  • the liquid crystal panel area 2 includes a sealing area 21 and an AA display area 22.
  • the AA display area 22 is the actual effective display area of the liquid crystal panel.
  • Step of making the image of the liquid crystal panel to be detected collecting the image of the liquid crystal panel to be detected in an overexposure state, and obtaining the gray scale value range of each area.
  • the method of collecting the image of the liquid crystal panel to be detected in the overexposure state is to remove the polarizing effect on the photographing lens 6 to make it appear in the overexposure state, so as to capture and obtain the image of the liquid crystal panel to be detected.
  • the method for removing the polarizing effect on the camera lens 6 is to drive the polarizer 61 on the camera lens to move away through the motor 7 or to drive the upper polarizer on the polarizer 61 on the camera lens through the motor 7 ( (Not shown) or the lower polarizer (not shown) rotated 90 degrees, so that the polarization direction of the upper polarizer and the lower polarizer are parallel without polarizing effect.
  • Using the motor 7 control can set the timing of removing the polarizing effect according to the cycle time of the beat, so as to be more intelligent and automated.
  • overexposure refers to the characteristic of making the screen completely white under a very large exposure time to highlight the boundary.
  • Each area in turn knows its backlight area 1 and liquid crystal panel area 2.
  • the detected defects include defects with abnormal cutting accuracy, which is to compare the edge boundary of the image of the liquid crystal panel to be inspected with the reference image, and to calculate the respective sides of the panel in the image of the liquid crystal panel to be inspected and the reference image
  • the predetermined value is in the range of 0.15 ⁇ 0.5mm.
  • the detected defects include cut convex edge convex corner defects, which are used to calculate the distance between the liquid crystal panel image to be inspected and the respective sides of the corresponding panel in the reference image, when any side of the liquid crystal panel area to be inspected
  • cut convex edge convex corner defects which are used to calculate the distance between the liquid crystal panel image to be inspected and the respective sides of the corresponding panel in the reference image, when any side of the liquid crystal panel area to be inspected
  • the distance value of the corresponding side of the comparison reference panel area is greater than the predetermined value, it belongs to a convex edge convex corner defect; wherein the predetermined value is in the range of 0.1-0.25 mm.
  • the detected defects include fragmentation defects, which is to calculate the distance between the liquid crystal panel image to be inspected and the corresponding sides of the panel in the comparison reference image, when any side of the liquid crystal panel area to be inspected is indented to the comparison reference When the distance value of the corresponding side of the panel area is greater than the predetermined value, it is a fragment defect; wherein the predetermined value is in the range of 0.1-0.25 mm.
  • calculating the side length deviation value of the respective sides of the liquid crystal panel to be tested and the comparison reference panel and calculating the distance between the respective sides of the liquid crystal panel to be tested and the comparison reference panel can be based on the actual length of each pixel of the liquid crystal panel to be tested and the camera lens 6 The proportional relationship of the actual length of each pixel of the photosensitive element 62 is calculated to obtain the actual defect length of the liquid crystal panel to be detected.
  • the LCD panel defect detection method further includes steps:
  • the step of counting the number of defective pixels the processing unit calculates the number of difference pixels of the liquid crystal panel to be detected and the comparison reference panel. When the number of difference pixels is greater than 5, it is the number of defective pixels of the liquid crystal panel to be detected. Detect the size of the number of defective pixels of the liquid crystal panel to divide the defect level.
  • the range of the number of difference pixels can be set according to the actual required accuracy, and the general setting range is 5-10.
  • dividing the defect level according to the size of the number of defective pixels of the liquid crystal panel to be detected specifically includes: according to step S4, the abnormal cutting accuracy defect 5, the convex edge defect 3, and the fragment defect 4 are respectively statistically calculated The number of defective pixels of the liquid crystal panel to be detected; or, the number of defective pixels of the liquid crystal panel to be detected is calculated according to the sum of the abnormal cutting accuracy defects 5, the convex corner defects 3, and the fragment defects 4 described in step S4; or, The number of defective pixels of the liquid crystal panel to be detected is calculated according to the weighted sum of the abnormal cutting accuracy defect 5, the convex corner defect 3, and the fragment defect 4 described in step S4.
  • the method of calculating the types of defects can be used to calculate the statistics of different types of defects.
  • the method of summing the types of defects can count the size of the total defect area for quick identification.
  • the weighted sum of the types of defects can be used to control the impact according to different weights. Degree to set.
  • the result of the defect level of the liquid crystal panel to be tested can generate a test report or report for easy reference.
  • Another embodiment of the present invention provides a defect detection system for a liquid crystal panel, and the device can implement any of the above detection methods.
  • FIGS. 4-5 Another embodiment of the present invention provides a liquid crystal panel defect detection system, including an API detection device (not shown), a camera lens 6, a motor 7, a backlight device 9, and a support structure 8 .
  • the API detection device (not shown) is used to process the received data and output the processing result.
  • the camera lens 6 is used to capture and obtain a comparison reference image and an image of a liquid crystal panel to be detected and send the image data to the API detection device (not shown).
  • the camera lens 6 includes a polarizer 61 and a photosensitive element 62
  • the motor 7 is used to move the polarizer 61 on the camera lens 6;
  • the backlight device 9 is used to provide a backlight when shooting, and the center of the backlight area 1 defined by the backlight device 9 is set opposite to the camera lens
  • the support structure 8 is located around the backlight device 9, and the area surrounded by the support structure 8 is opposite to the backlight area 1 defined by the backlight device 9.
  • the motor 7 control can be used to set the timing of rotating the polarizer 61 according to the cycle time of the cycle, so as to be more intelligent and automated.
  • the area range surrounded by the support structure 8 and the backlight area 1 are arranged relative to each other so that the camera lens 6 is not affected by the support structure 8, and the backlight area 1 is photographed intact, which can better identify and analyze.
  • the backlight provided by the backlight area 1 during shooting can illuminate the edge of the liquid crystal panel to be detected, so that the edge of the liquid crystal panel to be detected can be clearer when the image of the liquid crystal panel to be detected is produced in an overexposure state.
  • the present invention provides a method and device for detecting defects of a liquid crystal panel, which can automatically perform overexposure photography and image contrast detection, and also includes an API detection device, which can realize all functions of the burr inspection machine, so that it can pass
  • the LCD panel defect detection process can be realized by only adding a small number of production cycles, effectively reducing the overall production cycle, reducing equipment costs and labor costs, and the detection accuracy is more controllable, thereby improving the detection reliability.

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Abstract

一种液晶面板缺陷检测方法及其系统。液晶面板缺陷检测方法包括步骤：基准图像制作，待检测液晶面板图像制作，识别待检测液晶面板各区域，鉴别缺陷，以及统计缺陷像素数量。液晶面板缺陷检测系统包括API检测装置、拍照镜头(6)、马达(7)、背光区(1)和支撑结构(8)，其中拍照镜头(6)包括偏光片(61)、感光元件(62)。此系统可自动进行过曝光拍照和图像对比检测，同时能实现毛刺检查机台所有功能，有效地减少整体生产周期，降低设备成本和人力成本，提高了检测可靠性。

Description

一种液晶面板缺陷检测方法及其系统 技术领域
本发明涉及液晶面板缺陷检测技术领域，尤其是涉及一种液晶面板缺陷检测方法及其系统。
 背景技术
现行液晶显示屏（Liquid Crystal Display，LCD）产业中针对切割后的液晶面板边缘主要使用专业的毛刺检查（Burr check）设备来检测产品的边缘切割质量，确认有无破边（Chipping）、凸边凸角、平衡度不佳等缺陷。
其中常用的检测方式为使用API (Application Program Interface，应用程序接口)检测系统进行检测，其寻找液晶显示面板中的AA（Active Area，有效显示区域）显示区的方法为采样白画面，相机过曝，结合软件透过灰阶差区分密封（Seal）区与AA显示区后，人工检查各区域缺陷。
该检测方式需另行购置专业毛刺检查机台、产品传送设备，这在一定程度上增加了生产成本。进一步的，其最终需人工检测，而人工检测的准确率不可控，可靠性相对较低，而且检测工序周期长。
因此，确有必要来开发一种新型的检测方法及其系统，来克服现有技术中的缺陷。
 技术问题
为解决上述问题，本发明提供了一种液晶面板缺陷检测方法及其系统，可自动进行过曝拍照和图像对比检测，同时包含API检测装置，能实现毛刺检查机台所有功能，从而可以通过仅增加少量生产节拍就能实现液晶面板缺陷检测工序，有效减少整体生产周期，降低设备成本和人力成本，检测准确率更加可控，从而提高检测可靠性。
 技术解决方案
本发明的一个实施方式提供了一种液晶面板缺陷检测方法，所述检测方法包括：
S1、基准图像制作步骤，采集基准液晶面板各区域图像，对所述图像进行几何校正及滤波处理，作为对比基准图像，通过软件透过灰阶差区分出所述采集到的各区域图像中的背光（Backlight，BL）区和液晶面板区的边缘界限，记录每一区域像素灰阶值，界定各区域灰阶值范围；
S2、待检测液晶面板图像制作步骤，以过曝状态采集待检测液晶面板图像，并获得各区域的灰阶值范围；
S3、识别待检测液晶面板各区域步骤，将所述待检测液晶面板各区域图像与所述基准图像进行对比分析，根据所述基准图像各区域灰阶值范围识别所述待检测液晶面板图像中的各区域进而获知其背光区和液晶面板区；
S4、鉴别缺陷步骤，分析识别出的所述检测液晶面板区域图像四边的直线度，并与所述基准图像相应位置作比对，当两者的差值超过预定数值时，则认为所述待检测液晶面板存在缺陷，其中所述预定数值在0.1~0.5mm范围内。
进一步的，其中检测出的所述缺陷包括切割精度异常缺陷，其为对比待检测液晶面板图像与对比基准图像的边缘界限，计算所述待检测液晶面板图像中与对比基准图像中面板相应各边的边长偏差值，当任一边长偏差值大于所述预定数值时，其属于切割精度异常缺陷；其中所述预定数值在0.15~0.5mm范围内。
进一步的，其中检测出的所述缺陷包括切凸边凸角缺陷，其为计算待检测液晶面板图像与对比基准图像中相应面板各边的距离，当所述待检测液晶面板区任一边突出所述对比基准面板区相应边的距离数值大于所述预定数值时，其属于凸边凸角缺陷；其中所述预定数值在0.1-0.25mm范围内。
进一步的，其中检测出的所述缺陷包括破片缺陷，其为计算待检测液晶面板图像与对比基准图像中面板相应各边的距离，当所述待检测液晶面板区任一边缩进所述对比基准面板区相应边的距离数值大于所述预定数值时，其属于破片缺陷；其中所述预定数值在0.1-0.25mm范围内。
进一步的，液晶面板缺陷检测方法还包括步骤：
S5、统计缺陷像素数量步骤，在处理单元计算待检测液晶面板与对比基准面板的差异像素点数量，当所述差异像素点数量大于5时，为待检测液晶面板缺陷像素数量，根据所述待检测液晶面板缺陷像素数量的大小划分缺陷等级。
进一步的，其中步骤S5所述根据所述待检测液晶面板缺陷像素数量的大小划分缺陷等级具体包括：按照步骤S4所述切割精度异常缺陷、凸边凸角缺陷、破片缺陷分别统计计算得出所述待检测液晶面板缺陷像素数量；或，按照步骤S4所述所述切割精度异常缺陷、凸边凸角缺陷、破片缺陷求和计算得出所述待检测液晶面板缺陷像素数量；或，按照步骤S4所述切割精度异常缺陷、凸边凸角缺陷、破片缺陷加权求和计算得出所述待检测液晶面板缺陷像素数量。采用缺陷的类别分别计算的方式可实现不同类别缺陷分别统计，采用缺陷的类别求和计算的方式可统计总的缺陷区域大小便于快速鉴别，采用缺陷的类别加权求和计算可根据不同权重对照影响程度来设置。
进一步的，其中步骤S2所述以过曝状态采集待检测液晶面板图像的方式是将拍照镜头上的偏光效果去除，使其呈现过曝状态，从而拍摄获得待检测液晶面板图像。
进一步的，其中所述将拍照镜头上的偏光效果去除的方式是通过马达驱动所述拍照镜头上的偏光片移开，或通过马达驱动所述拍照镜头上的偏光片的上偏光片或下偏光片旋转90度，使上偏光片与下偏光片偏振方向平行而不具有偏光效果。
本发明的一个实施方式提供了一种液晶面板缺陷检测系统，包括API检测装置、拍照镜头、马达、背光区和支撑结构。其中所述API检测装置用于处理接收的数据和输出处理结果。所述拍照镜头用于拍摄获得对比基准图像和待检测液晶面板图像并将所述图像数据发送给所述API检测装置，所述拍照镜头包括偏光片(Polarizer，POL）、感光元件；所述马达用于将拍照镜头上的偏光片移动；所述背光装置用于拍摄时提供背光源，所述背光装置定义的背光区的中心与所述拍照镜头相对设置；所述支撑结构位于所述背光装置的周围，所述支撑结构围成的区域范围与所述背光装置定义的背光区相对设置。
其中，采用马达控制可根据节拍时间周期来设定转动偏光片的时机，从而更智能和自动化。支撑结构围成的区域范围与所述背光区相对设置可以使拍照镜头不受支撑结构的影响，把背光区拍摄完整，能更好的识别分析。背光区在拍摄时提供的背光源可将待检测液晶面板的边缘照亮，使待检测液晶面板图像制作时过曝状态采集待检测液晶面板图像边缘更清晰。
 有益效果
本发明的有益效果是：本发明提供了一种液晶面板缺陷检测方法及其装置，可自动进行过曝拍照和图像对比检测，同时包含API检测装置，能实现毛刺检查机台所有功能，从而可以通过仅增加少量生产节拍就能实现液晶面板缺陷检测工序，有效减少整体生产周期，降低设备成本和人力成本，检测准确率更加可控，从而提高检测可靠性。
 附图说明
图1 为本发明第一实施例的液晶面板缺陷检测方法的流程图；
图2 为本发明第二实施例的液晶面板缺陷检测方法的流程图；
图3 为本发明第三实施例的待检测液晶面板图像与基准图像对比示意图；
图4 为本发明第四实施例的液晶面板缺陷检测系统主视图；
图5 为本发明第五实施例的液晶面板缺陷检测系统俯视图。
图中部件标识如下：
1、背光区，      2、液晶面板区， 3、凸边凸角，  4、破片，
5、切割精度异常，6、拍照镜头，   7、马达，      8、支撑结构，
9、背光装置，    21、密封区，    22、AA显示区，61、偏光片，
62、感光元件。
 本发明的实施方式
本发明的一个实施方式提供了液晶面板缺陷检测方法，请参阅图1、图3所示，所述检测方法包括：
S1、基准图像制作步骤，采集基准液晶面板各区域图像，对所述图像进行几何校正及滤波处理，作为对比基准图像，通过软件透过灰阶差区分出所述采集到的各区域图像中的背光区1和液晶面板区2的边缘界限，记录每一区域像素灰阶值，界定各区域灰阶值范围。
其中，液晶面板区2包括密封区21和AA显示区22，AA显示区22为液晶面板的实际有效显示区域。
S2、待检测液晶面板图像制作步骤，以过曝状态采集待检测液晶面板图像，并获得各区域的灰阶值范围。
其中，所述以过曝状态采集待检测液晶面板图像的方式是将拍照镜头6上的偏光效果去除，使其呈现过曝状态，从而拍摄获得待检测液晶面板图像。其中所述将拍照镜头6上的偏光效果去除的方式是通过马达7驱动所述拍照镜头上的偏光片61移开，或通过马达7驱动所述拍照镜头上的偏光片61的上偏光片（图未示）或下偏光片（图未示）旋转90度，使上偏光片与下偏光片偏振方向平行而不具有偏光效果。采用马达7控制可根据节拍时间周期来设定偏光效果去除的时机，从而更智能和自动化。其中，过曝是指极大的曝光时间下使画面呈现全白的特性，用以凸显边界。
S3、识别待检测液晶面板各区域步骤，将所述待检测液晶面板各区域图像与所述基准图像进行对比分析，根据所述基准图像各区域灰阶值范围识别所述待检测液晶面板图像中的各区域进而获知其背光区1和液晶面板区2。
S4、分析识别出的所述检测液晶面板区域图像四边的直线度，并与所述基准图像相应位置作比对，当两者的差值超过预定数值时，则认为所述待检测液晶面板存在缺陷，其中所述预定数值在0.1~0.5mm范围内。
进一步的，其中检测出的所述缺陷包括切割精度异常缺陷，其为对比待检测液晶面板图像与对比基准图像的边缘界限，计算所述待检测液晶面板图像中与对比基准图像中面板相应各边的边长偏差值，当任一边长偏差值大于所述预定数值时，其属于切割精度异常缺陷；其中所述预定数值在0.15~0.5mm范围内。
进一步的，其中检测出的所述缺陷包括切凸边凸角缺陷，其为计算待检测液晶面板图像与对比基准图像中相应面板各边的距离，当所述待检测液晶面板区任一边突出所述对比基准面板区相应边的距离数值大于所述预定数值时，其属于凸边凸角缺陷；其中所述预定数值在0.1-0.25mm范围内。
进一步的，其中检测出的所述缺陷包括破片缺陷，其为计算待检测液晶面板图像与对比基准图像中面板相应各边的距离，当所述待检测液晶面板区任一边缩进所述对比基准面板区相应边的距离数值大于所述预定数值时，其属于破片缺陷；其中所述预定数值在0.1-0.25mm范围内。
进一步的，计算待检测液晶面板与对比基准面板相应各边的边长偏差值和计算待检测液晶面板与对比基准面板相应各边的距离可根据待检测液晶面板每像素实际长度与拍照镜头6的感光元件62每像素实际长度的比例关系计算得出待检测液晶面板实际缺陷长度。
请参阅图2所示，液晶面板缺陷检测方法还包括步骤：
S5、统计缺陷像素数量步骤，在处理单元计算待检测液晶面板与对比基准面板的差异像素点数量，当所述差异像素点数量大于5时，为待检测液晶面板缺陷像素数量，根据所述待检测液晶面板缺陷像素数量的大小划分缺陷等级。所述差异像素点数量范围可根据实际要求精度设定，一般设定范围为5-10。
其中，所述根据所述待检测液晶面板缺陷像素数量的大小划分缺陷等级具体包括：按照步骤S4所述切割精度异常缺陷5、凸边凸角缺陷3、破片缺陷4分别统计计算得出所述待检测液晶面板缺陷像素数量；或，按照步骤S4所述所述切割精度异常缺陷5、凸边凸角缺陷3、破片缺陷4求和计算得出所述待检测液晶面板缺陷像素数量；或，按照步骤S4所述切割精度异常缺陷5、凸边凸角缺陷3、破片缺陷4加权求和计算得出所述待检测液晶面板缺陷像素数量。采用缺陷的类别分别计算的方式可实现不同类别缺陷分别统计，采用缺陷的类别求和计算的方式可统计总的缺陷区域大小便于快速鉴别，采用缺陷的类别加权求和计算可根据不同权重对照影响程度来设置。
另外，该待检测液晶面板的缺陷等级的结果可生成检测报表或报告，以便查阅。
本发明的另一个实施方式提供了一种液晶面板缺陷检测系统，所述装置能够实现上述任一项的检测方法。
请参阅图4-图5所示本发明的另一个实施方式提供了一种液晶面板缺陷检测系统，包括API检测装置（图未示）、拍照镜头6、马达7、背光装置9和支撑结构8。其中所述API检测装置（图未示）用于处理接收的数据和输出处理结果。所述拍照镜头6用于拍摄获得对比基准图像和待检测液晶面板图像并将所述图像数据发送给所述API检测装置（图未示），所述拍照镜头6包括偏光片61、感光元件62；所述马达7用于将拍照镜头6上的偏光片61移动；所述背光装置9用于拍摄时提供背光源，所述背光装置9定义的背光区1的中心与所述拍照镜头相对设置；所述支撑结构8位于所述背光装置9的周围，所述支撑结构8围成的区域范围与所述背光装置9定义的背光区1相对设置。
其中，采用马达7控制可根据节拍时间周期来设定转动偏光片61的时机，从而更智能和自动化。支撑结构8围成的区域范围与所述背光区1相对设置可以使拍照镜头6不受支撑结构8的影响，把背光区1拍摄完整，能更好的识别分析。背光区1在拍摄时提供的背光源可将待检测液晶面板的边缘照亮，使待检测液晶面板图像制作时过曝状态采集待检测液晶面板图像边缘更清晰。
本发明的有益效果是：本发明提供了一种液晶面板缺陷检测方法和装置，可自动进行过曝拍照和图像对比检测，同时包含API检测装置，能实现毛刺检查机台所有功能，从而可以通过仅增加少量生产节拍就能实现液晶面板缺陷检测工序，有效减少整体生产周期，降低设备成本和人力成本，检测准确率更加可控，从而提高检测可靠性。
以上所述仅是本发明的优选实施方式，应当指出，对于本技术领域的普通技术人员，在不脱离本发明原理的前提下，还可以做出若干改进和润饰，这些改进和润饰也应视为本发明的保护范围。

Claims (10)

  1. 一种液晶面板缺陷检测方法，其中，所述检测方法包括：
    S1、基准图像制作步骤，采集基准液晶面板各区域图像，对所述图像进行几何校正及滤波处理，作为对比基准图像，通过软件透过灰阶差区分出所述采集到的各区域图像中的背光区和液晶面板区的边缘界限，记录每一区域像素灰阶值，界定各区域灰阶值范围；
    S2、待检测液晶面板图像制作步骤，以过曝状态采集待检测液晶面板图像，并获得各区域的灰阶值范围；
    S3、识别待检测液晶面板各区域步骤，将所述待检测液晶面板各区域图像与所述基准图像进行对比分析，根据所述基准图像各区域灰阶值范围识别所述待检测液晶面板图像中的各区域进而获知其背光区和液晶面板区；
    S4、鉴别缺陷步骤，分析识别出的所述检测液晶面板区域图像四边的直线度，并与所述基准图像相应位置作比对，当两者的差值超过预定数值时，则认为所述待检测液晶面板存在缺陷，其中所述预定数值在0.1~0.5mm范围内。
  2. 根据权利要求1所述的液晶面板缺陷检测方法，其中，步骤S4中检测出的所述缺陷包括切割精度异常缺陷，其为对比待检测液晶面板图像与对比基准图像的边缘界限，计算所述待检测液晶面板图像中与对比基准图像中面板相应各边的边长偏差值，当任一边长偏差值大于所述预定数值时，其属于切割精度异常缺陷；其中所述预定数值在0.15~0.5mm范围内。
  3. 根据权利要求1所述的液晶面板缺陷检测方法，其中，步骤S4中检测出的所述缺陷包括切凸边凸角缺陷，其为计算待检测液晶面板图像与对比基准图像中相应面板各边的距离，当所述待检测液晶面板区任一边突出所述对比基准面板区相应边的距离数值大于所述预定数值时，其属于凸边凸角缺陷；其中所述预定数值在0.1-0.25mm范围内。
  4. 根据权利要求1所述的液晶面板缺陷检测方法，其中，步骤S4中检测出的所述缺陷包括破片缺陷，其为计算待检测液晶面板图像与对比基准图像中面板相应各边的距离，当所述待检测液晶面板区任一边缩进所述对比基准面板区相应边的距离数值大于所述预定数值时，其属于破片缺陷；其中所述预定数值在0.1-0.25mm范围内。
  5. 根据权利要求1所述的液晶面板缺陷检测方法，其中，还包括步骤：
    S5、统计缺陷像素数量步骤，在处理单元计算待检测液晶面板与对比基准面板的差异像素点数量，当所述差异像素点数量大于5时，为待检测液晶面板缺陷像素数量，根据所述待检测液晶面板缺陷像素数量的大小划分缺陷等级。
  6. 根据权利要求5所述的液晶面板缺陷检测方法，其中，步骤S5所述根据所述待检测液晶面板缺陷像素数量的大小划分缺陷等级具体包括：
    按照步骤S4所述切割精度异常缺陷、凸边凸角缺陷、破片缺陷分别统计计算得出所述待检测液晶面板缺陷像素数量。
  7. 根据权利要求5所述的液晶面板缺陷检测方法，其中，步骤S5所述根据所述待检测液晶面板缺陷像素数量的大小划分缺陷等级具体包括：
    按照步骤S4所述切割精度异常缺陷、凸边凸角缺陷、破片缺陷加权求和计算得出所述待检测液晶面板缺陷像素数量。
  8. 根据权利要求1所述的液晶面板缺陷检测方法，其中，步骤S2所述以过曝状态采集待检测液晶面板图像的方式是将拍照镜头上的偏光效果去除，使其呈现过曝状态，从而拍摄获得待检测液晶面板图像。
  9. 根据权利要求8所述的液晶面板缺陷检测方法，其中，所述将拍照镜头上的偏光效果去除的方式是通过马达驱动所述拍照镜头上的偏光片移开，或通过马达驱动所述拍照镜头上的偏光片的上偏光片或下偏光片旋转90度，使上偏光片与下偏光片偏振方向平行而不具有偏光效果。
  10. 一种液晶面板缺陷检测系统，其中，包括：
    API检测装置，用于处理接收的数据和输出处理结果；
    拍照镜头，用于拍摄获得对比基准图像和待检测液晶面板图像并将所述图像数据发送给所述API检测装置，所述拍照镜头包括偏光片、感光元件；
    马达，用于将拍照镜头上的偏光片移动；
    背光装置，用于拍摄时提供背光源，所述背光装置定义的背光区的中心与所述拍照镜头相对设置；
    支撑结构，位于所述背光装置的周围，所述支撑结构围成的区域范围与所述背光装置定义的背光区相对设置。
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