基于视觉的液晶屏/OLED屏缺陷检测方法综述  

Vision-based LCD/OLED defect detection methods:a critical summary

作　　者：林思媛 吴一全[1] Lin Siyuan;Wu Yiquan(College of Electronic and Information Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 211106,China)

机构地区：[1]南京航空航天大学电子信息工程学院,南京211106

出　　处：《中国图象图形学报》2024年第5期1321-1345,共25页Journal of Image and Graphics

基　　金：国家自然科学基金项目(61573183)。

摘　　要：液晶屏(liquid crystal display, LCD)和有机发光半导体(organic light-emitting diode, OLED)屏的制造工艺复杂,其生产过程的每个阶段会不可避免地引入各种缺陷,影响产品的视觉效果及用户体验,甚至出现严重的质量问题。实现快速且精确的缺陷检测是提高产品质量和生产效率的重要手段。本文综述了近20年来基于机器视觉的液晶屏/OLED屏缺陷检测方法。首先给出了液晶屏/OLED屏表面缺陷的定义、分类及其产生的原因和缺陷的量化指标;指出了基于视觉的液晶屏/OLED屏表面缺陷检测的难点。然后重点阐述了基于图像处理的缺陷检测方法,包括介绍图像去噪和图像亮度矫正的图像预处理过程;考虑到所采集的液晶屏/OLED屏图像存在纹理背景干扰,对重复性纹理背景消除和背景抑制法进行分析;针对Mura缺陷边缘模糊等特点,总结改进的缺陷分割方法;阐述提取图像特征并使用支持向量机、支持向量数据描述和随机森林算法等基于特征识别的缺陷检测方法。接着综述了基于深度学习的缺陷检测方法,根据产线不同时期的样本数量分别总结了无监督学习、缺陷样本生成、迁移学习和监督学习的方法,其中无监督学习从基于生成对抗网络和自编码器两个方面进行阐述。随后梳理了通用纹理表面缺陷数据集和模型性能的评价指标。最后针对目前液晶屏/OLED屏缺陷检测方法存在的问题,对未来进一步的研究方向进行了展望。The new display industry is an important foundation for strategic emerging information industries.Under the active guidance and continuous investment of various national industrial policies,China’s new display industry has rapidly developed and has become one of the most dynamic industries.The industry scale accounts for up to 40%of the global dis⁃play industry,ranking first in the world.Under the background of the current digital information age,the demand for con⁃sumer electronics,such as smart phones,tablets,computers,displays,and televisions,in various occasions,is con⁃stantly rising.This phenomenon results in a yearly rising trend in the global demand for liquid crystal display(LCD)and organic light-emitting diode(OLED)screens and other display panels.The manufacturing process of LCD and OLED is complex,and every stage of the production process will inevitably produce various defects,affecting the visual effect and user experience and even leading to serious quality problems.Fast and accurate defect detection is crucial to improving product quality and production efficiency.Therefore,the defect detection in the production process of LCD and OLED is necessary. This article reviews the research progress of defect detection methods for LCD/OLED based on machine vision inthe past 20 years to provide valuable reference. First, the structure and manufacturing process of commonly used TFT-LCDand OLED are given. The defects on the surface of the LCD/OLED are classified in accordance with the causes of defects,defect size, and defect shape. The definitions of the defects are presented, and the causes of the defects are brieflydescribed. The quantitative indicators of defects SEMU and DSEMU are given. The difficulties of surface defect detectionof LCD/OLED screens based on machine vision are also explained. This paper focuses on the defect detection methodsbased on image processing. In actual production, the images to be detected are captured by industrial cameras, and theirimages are easily affected by noise

关 键 词：缺陷检测 液晶屏(LCD) OLED屏 机器视觉 深度学习 纹理背景消除 无监督学习 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] TN27[自动化与计算机技术—计算机科学与技术]