基于自适应局部增强的手机TFT-LCD屏Mura缺陷自动检测

廖苗; 刘毅志; 欧阳军林; 余建勇; 肖文辉; 彭理

doi:10.3788/YJYXS20183306.0475

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基于自适应局部增强的手机TFT-LCD屏Mura缺陷自动检测

材料与器件 | 更新时间：2020-07-06

- 基于自适应局部增强的手机TFT-LCD屏Mura缺陷自动检测
- Automatic detection of Mura defect in TFT-LCD mobile screen based on adaptive local enhancement
- 液晶与显示 2018年33卷第6期页码：475-482
- 作者机构：
  
  湖南科技大学计算机科学与工程学院, 湖南湘潭 411100
- 作者简介：
  
  [ "廖苗(1988-) ,女,湖南常德人,博士,讲师,主要研究方向:数字图像处理、模式识别与人工智能。E-mail:liaomiaohi@163.com" ]
  [ "刘毅志(1973-)，男，湖南衡阳人，博士，副教授，主要研究方向：数字图像处理、多媒体内容分析。E-mail:yizhi_liu@sina.cn" ]
  [ "欧阳军林(1977-)，男，湖南湘乡人，博士，讲师，主要研究方向：数字图像取证，深度学习。E-mail:yangjunlin0732@163.com" ]
  [ "余建勇(1975-)，男，湖南醴陵人，博士，讲师，主要研究方向：机器学习、多智能系统。E-mail:yujyong@hnust.edu.cn" ]
  [ "肖文辉(1981-)，女，湖南双峰人，博士生，讲师，主要研究方向：数字图像处理。E-mail: whxiao@hnust.edu.cn" ]
  [ "彭理(1981-)，女，湖南长沙人，博士生，讲师，主要研究方向：机器学习、生物信息处理。E-mail: plpeng@hnu.edu.cn" ]
- 基金信息：
  
  国家自然科学基金资助项目(61702179);湖南省自然科学基金资助项目(2017JJ3091);湖南省自然科学基金资助项目(2016JJ2057);湖南省教育厅资助科研项目(17C0643);湖南省教育厅资助科研项目(15C0546);湖南科技大学校级科研项目(E51754);中国博士后科学基金资助项目(2018M632994);中南大学博士后基金(202594);the National Natural Science Foundation of China(61702179);Hunan Provincial Natural Science Foundation of China(2017JJ3091);Hunan Provincial Natural Science Foundation of China(2016JJ2057);Scientific Research Fund of Hunan Provincial Education Department(17C0643);Scientific Research Fund of Hunan Provincial Education Department(15C0546);Scientific Research Fund of Hunan University of Science and Technology(E51754);China Postdoctoral Science Foundation funded project(2018M632994);Postdoctoral Foundation of Central South University(202594)
- DOI：10.3788/YJYXS20183306.0475
  中图分类号： TP391
- 收稿日期：2018-01-18，
  
  录用日期：2018-4-2，
  
  纸质出版日期：2018-06
- 稿件说明：
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廖苗, 刘毅志, 欧阳军林, 等. 基于自适应局部增强的手机TFT-LCD屏Mura缺陷自动检测[J]. 液晶与显示, 2018,33(6):475-482.

Miao LIAO, Yi-zhi LIU, YANG Jun-lin OU, et al. Automatic detection of Mura defect in TFT-LCD mobile screen based on adaptive local enhancement[J]. Chinese journal of liquid crystals and displays, 2018, 33(6): 475-482.
廖苗, 刘毅志, 欧阳军林, 等. 基于自适应局部增强的手机TFT-LCD屏Mura缺陷自动检测[J]. 液晶与显示, 2018,33(6):475-482. DOI： 10.3788/YJYXS20183306.0475.

Miao LIAO, Yi-zhi LIU, YANG Jun-lin OU, et al. Automatic detection of Mura defect in TFT-LCD mobile screen based on adaptive local enhancement[J]. Chinese journal of liquid crystals and displays, 2018, 33(6): 475-482. DOI： 10.3788/YJYXS20183306.0475.

摘要

针对手机屏幕图像整体亮度不均以及Mura缺陷对比度低等特点，提出一种基于自适应局部增强的Mura缺陷自动在线检测方法。首先对CCD相机采集的手机屏幕原始图像进行感兴趣区域提取、几何校正、滤波等预处理，获取图像中的屏幕区域，然后将屏幕区域划分为多个不重叠的像素块，并根据每个像素块的灰度分布特征，采用自适应局部增强算法自动识别并定位图像中的Mura区域，最后考虑到Mura缺陷大小的不确定，提出采用多层级分块的方式对屏幕区域进行检测，提高算法鲁棒性。实验结果表明，相较现有多种屏幕缺陷自动检测算法，本文方法能更准确有效地识别手机屏幕中的Mura缺陷，且覆盖率和误检率分别为91.17%和5.84%。

Abstract

Aiming at the characteristics of mobile screen image

such as non-uniform luminance and low contrast of Mura defect

an automatic on-line detection method for Mura defect based on adaptive local enhancement is proposed in this paper. First

for the original mobile screen image captured by CCD camera

preprocessing steps including region of interest extraction

geometric correction and filtering are applied to extract the screen region from the original image. Then

the screen region is divided into multiple non-overlapping pixel blocks

and the Mura regions in each block are recognized and located by adaptive local enhancement according to the intensity distribution of each block. Finally

to increase the robustness of the algorithm

a multi-level partitioning scheme is proposed in this paper to detect the Mura defects with different sizes. Experimental results show that

compared to many automatic screen defect detection methods

the proposed method can detect the Mura defects from mobile screen more accurately and effectively

and the percentages of overlapping and detection error are 91.17% and 5.84%

respectively.

关键词

Keywords

references

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