Automatic Detection of Region-Mura Defect in TFT-LCD

Jae Yeong LEE  Suk In YOO  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E87-D   No.10   pp.2371-2378
Publication Date: 2004/10/01
Online ISSN: 
DOI: 
Print ISSN: 0916-8532
Type of Manuscript: PAPER
Category: Image Processing and Video Processing
Keyword: 
machine vision,  image segmentation,  regression diagnostics,  industrial inspection,  visual perception,  

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Summary: 
Visual defects, called mura in the field, sometimes occur during the manufacturing of the flat panel liquid crystal displays. In this paper we propose an automatic inspection method that reliably detects and quantifies TFT-LCD region-mura defects. The method consists of two phases. In the first phase we segment candidate region-muras from TFT-LCD panel images using the modified regression diagnostics and Niblack's thresholding. In the second phase, based on the human eye's sensitivity to mura, we quantify mura level for each candidate, which is used to identify real muras by grading them as pass or fail. Performance of the proposed method is evaluated on real TFT-LCD panel samples.