自动光学检测的彩膜分区检查与判定

张铁轶; 余道平; 王野; 刘超强; 张祥

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自动光学检测的彩膜分区检查与判定

器件物理及器件制备技术 | 更新时间：2020-08-12

- 自动光学检测的彩膜分区检查与判定
- Color filter partition inspection and judgment of automatic optical inspection
- 液晶与显示 2014年29卷第1期页码：34-39
- 作者机构：
  
  北京京东方显示技术有限公司北京,中国,100176
- 作者简介：
- 基金信息：
  
  安徽省2012科技计划资助项目（No.1206c0805007）()
- DOI：
  中图分类号： TH865;TH691.9
- 收稿日期：2013-01-22，
  
  修回日期：2013-03-27，
  
  纸质出版日期：2014-02-15
- 稿件说明：
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张铁轶, 余道平, 王野, 刘超强, 张祥. 自动光学检测的彩膜分区检查与判定[J]. 液晶与显示, 2014,29(1): 34-39

ZHANG Tie-yi, YU Dao-ping, WANG Ye, LIU Chao-qiang, ZHANG Xiang. Color filter partition inspection and judgment of automatic optical inspection[J]. , 2014,29(1): 34-39
张铁轶, 余道平, 王野, 刘超强, 张祥. 自动光学检测的彩膜分区检查与判定[J]. 液晶与显示, 2014,29(1): 34-39 DOI：

ZHANG Tie-yi, YU Dao-ping, WANG Ye, LIU Chao-qiang, ZHANG Xiang. Color filter partition inspection and judgment of automatic optical inspection[J]. , 2014,29(1): 34-39 DOI：

摘要

为了提高自动光学检测系统检测彩膜质量的准确率，降低误判，通过分析由红绿蓝三色组成矩阵结构和Line CCD获取的彩膜图像特征，在五点周期比较检测的基础上设计一种彩膜缺陷的检测方法。该方法通过对彩膜的机械与光学对位后，通过五点比对进行缺陷的检测。Line CCD从红绿蓝3个不同的区域获取不同的灰阶值，分别设置3个区域的灰阶值范围和该区域的判定阈值；最后根据缺陷与正常点灰阶差值的不同对缺陷进行分类，赋予相应的缺陷代码。基于以上3个步骤，实现对整张彩膜的缺陷检测。实验结果表明，采用五点比较、分区检测和缺陷分类相结合的方法，缺陷检出的准确率可以提高至99.6%以上。

Abstract

In order to improve the inspection accuracy and reduce misjudgment rate for the color filter quality inspection in an automatic optical inspection system

a defect inspection method for color filter was proposed based on analyzing the color filter image acquired by the red

green and blue color matrix structure and Line CCD. Three steps were used to detect the defect of color filter. Defects of color filter were inspected firstly by the five points comparison method after mechanical and optical alignment for color filter.Then

according to Line CCD obtained by three different grayscale values from the red

green and blue area

the determination threshold are respectively provided in the three regions. Finally

the defects were classified depending on the grayscale difference in the defect and the normal point

and the corresponding defect code is given. The experiment results show that the proposed method composed of the five points comparison method

partition detection

defect classification can make inspection accuracy reach more than 99.6%.

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references

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