Affiliation:
1. Guangdong University of Technology
Abstract
TFT-LCD panel defect detection has been one of the difficulties in this field because of fuzzy defect boundary, low contrast between defects and background, and low detection speed. The structure of TFT-LCD panels and classification are introduced. Through the analysis of panel defect features, current detection methods for the TFT-LCD panel defects are reviewed. The key technologies of feature extraction and defect classification are analyzed in the defect image recognition of TFT-LCD panel. Meanwhile the methods of fuzzy boundary defect segmentation, image subtraction and image filtering are also discussed. Finally, the characteristics and advantages of these detection methods are concluded, and several key issues for the TFT-LCD defect detection have been proposed for future development.
Publisher
Trans Tech Publications, Ltd.
Reference18 articles.
1. Tsai D M, Hung C Y. International journal of production research, 2005, 43 (21): 4589-4607.
2. Tsai D M, Chuang S T, Tseng Y H. International journal of production research, 2007, 45 (6): 1297-1321.
3. Bi X. Study on the methods of machine vision inspection for the mura defect of TFT-LCD process [D]. Shanghai：Shanghai Jiaotong University, 2008. (In Chinese).
4. Zhang Y. Research on Mura inspection technology of TFT-LCD based on machine vision [D]. Harbin：Harbin Institute of Technology, 2006. (In Chinese).
5. Yi H L, Szu H L, Yi L H, et al. Expert Systems with Applications, 2009, 36 (2): 1978-(1998).
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