• CN:11-2187/TH
  • ISSN:0577-6686

›› 2010, Vol. 46 ›› Issue (12): 13-19.

• 论文 • 上一篇    下一篇

TFT-LCD Mura缺陷机器视觉检测方法

毕昕;丁汉   

  1. 上海交通大学机械与动力工程学院
  • 发布日期:2010-06-20

Machine Vision Inspection Method of Mura Defect for TFT-LCD

BI Xin;DING Han   

  1. School of Mechanical Engineering, Shanghai Jiao Tong University
  • Published:2010-06-20

摘要: 针对液晶显示器(Liquid crystal display,LCD)制程中Mura缺陷检测的重要性和人工检测的弊端,研究TFT-LCD Mura 缺陷的机器视觉自动检测方法。基于国际半导体设备与材料组织(Semiconductor Equipment and Materials International,SEMI)标准中Mura缺陷的测量规范和LCD视觉检测试验平台,针对Mura缺陷边缘模糊、对比度低、图像中存在重复纹理背景和整体的亮度不均匀等特点,分别研究基于实值Gabor小波滤波的纹理背景抑制方法、基于同态变换和独立分量分析的亮度不均匀校正方法、基于主动轮廓模型和水平集方法的缺陷分割以及基于SEMI标准的缺陷量化方法,综合几个方面的研究,建立Mura缺陷自动检测流程。检测试验证明,所提出方法能较好地抑制纹理背景、校正背景亮度不均匀和莫尔条纹,准确的分割缺陷并进行量化评定。该方法适用于Mura缺陷的自动检测,检测方法与人的视觉特性相似,具有较好的鲁棒性。对于50个带有Mura缺陷的LCD样本,有48个样本被成功检测。

关键词: Gabor滤波, Mura缺陷, 独立分量分析, 水平集, 主动轮廓模型

Abstract: The automatic machine vision inspection way is studied for the Mura defect of TFT-LCD, aiming at the importance of defect inspection and the shortcoming of manual inspection in liquid crystal display (LCD) process. Mura is local lightness variation with low contrast, blurry contour, uneven brightness and textured background. Based on the Semiconductor Equipment and Materials International (SEMI) standard for Mura and the LCD vision inspection platform, the inspection algorithms are researched, including the textured background suppression method using real Gabor filtering, the adjustment of brightness unevenness with homomorphic transform and independent component analysis, the Mura segmentation using active contour model and level set method and the Mura quantification based on SEMI standard. The automatic inspection process is set up by synthesizing the researches proposed above. The inspection experiments show that the proposed method can suppress the textured background, eliminate the unevenness and moire fringe in background, accurately segment defects and carry out quantitative evaluation. The proposed method is applicable to automatic inspection of Mura defect with good robustness and similar to vision characteristic of human eyes. And, for 50 LCD samples, 48 samples are inspected accurately.

Key words: Active contour model, Gabor filtering, Independent component analysis, Level set, Mura defect

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