Detection of Local Mura Defects in TFT-LCD Using Machine Vision

Machine vision is widely used in the field of defect inspection. Mura is a typical defect of LCD panel, appearing as local lightness variation with low contrast and blurry contour, so it is hard to be inspected with traditional thresholding or edge detection methods. This paper presents a machine vision Mura inspection method based on real Gabor filter. By selecting appropriate number of filtering scale and orientation, a set of real Gabor filter are formed and applied to the LCD images with defects. Then, through images fusion, all the sub-images from different channels are fused together and as a result, the global structurally textured backgrounds are eliminated and the local defects are preserved. As expected, the final binary images show the defects out. Experiments show that this method is suitable to the inspection of many types of Mura. Furthermore, it is insensitive to the rotation of image.

[1]  Josef Kittler,et al.  Audio- and Video-Based Biometric Person Authentication, 5th International Conference, AVBPA 2005, Hilton Rye Town, NY, USA, July 20-22, 2005, Proceedings , 2005, AVBPA.

[2]  Du-Ming Tsai,et al.  Automatic defect inspection for LCDs using singular value decomposition , 2005 .

[3]  Lakhmi C. Jain,et al.  Knowledge-Based Intelligent Information and Engineering Systems , 2004, Lecture Notes in Computer Science.

[4]  Anil K. Jain,et al.  Unsupervised texture segmentation using Gabor filters , 1990, 1990 IEEE International Conference on Systems, Man, and Cybernetics Conference Proceedings.

[5]  Jae Yeong Lee,et al.  Automatic Detection of Region-Mura Defect in TFT-LCD , 2004, IEICE Trans. Inf. Syst..

[6]  P Perona,et al.  Preattentive texture discrimination with early vision mechanisms. , 1990, Journal of the Optical Society of America. A, Optics and image science.

[7]  Wilson S. Geisler,et al.  Multichannel Texture Analysis Using Localized Spatial Filters , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  Chengjun Liu,et al.  Face Recognition Using Independent Gabor Wavelet Features , 2001, AVBPA.

[9]  D. G. Albrecht,et al.  Spatial frequency selectivity of cells in macaque visual cortex , 1982, Vision Research.

[10]  J. Daugman Two-dimensional spectral analysis of cortical receptive field profiles , 1980, Vision Research.

[11]  Kil-Houm Park,et al.  Morphological Blob-Mura Defect Detection Method for TFT-LCD Panel Inspection , 2004, KES.