Low-contrast surface inspection of mura defects in TFT-LCDsusing Independent Component Analysis and Wavelet Transform

• Main Authors: Jia-Lin Chen, 陳嘉霖
• Other Authors: Du-Ming Tsai
• Format: Others
• Language: zh-TW
• Published: 2007
• Online Access: http://ndltd.ncl.edu.tw/handle/40189020988807459094

碩士 === 元智大學 === 工業工程與管理學系 === 95 === This research proposes a machine vision method for detecting non-uniform brightness defects, called mura, in TFT-LCD manufacturing. Mura will cause bright or black blocks when LCD panels are switched on. It has low-contrast and uneven brightness properties, and causes inspection difficult in 2D images. By horizontally and vertically scanning the 2D image of an LCD surface, the 1D gray-level profiles between faultless and defective line images can be well distinguished. One-dimensional inspection schemes are, therefore, proposed for mura detection in low-contrast images. The proposed method in this study involves two detection stages. Independent component analysis (ICA) is adopted first to design filters that can best represent the global features of faultless line images. The first detection stage uses the convolution filters to identify suspected line images. In the second detection stage, the potential defect line images are evaluated, and the true defect location is detected using the high-pass Haar wavelet decomposition. The proposed method involves only convolution operations in the two detection stage, and is very computationally efficient. The experimental results have shown the efficacy of the proposed method for a number of LCD panels and color filters that contain various defect sizes and shapes including spot-, line-, ring- and gravity-mura.