Defect detection method for TFT-LCD panel based on saliency map model

TFT-LCD can have many defects caused by problems with color filter, TFT array, etc. In this paper, we propose a defect detection algorithm for TFT-LCD panel based on saliency map. Saliency map finds attentional spotlight using three features - color, orientation, intensity. In this work, input images are obtained from the 8 bit grayscale line scan camera. Because the input images are grayscale, we use periodicity that comes from pixels of TFT-LCD panel and edge operation instead of color information. Some defects of practical defective panel image are too faint to discriminate between normal and abnormal. Experimental results show that our algorithm can distinguish faint defect from poor image.

[1]  C. Koch,et al.  A saliency-based search mechanism for overt and covert shifts of visual attention , 2000, Vision Research.

[2]  Jae Wook Jeon,et al.  A high-speed high-resolution vision system for the inspection of TFT LCD , 2001, ISIE 2001. 2001 IEEE International Symposium on Industrial Electronics Proceedings (Cat. No.01TH8570).

[3]  Yillbyung Lee,et al.  A Saliency Map Model for Color Images using Statistical Information and Local Competitive Relations of Extracted Features , 2002 .

[4]  S Ullman,et al.  Shifts in selective visual attention: towards the underlying neural circuitry. , 1985, Human neurobiology.

[5]  K. Nakashima.  Hybrid inspection system for LCD color filter panels , 1994, Conference Proceedings. 10th Anniversary. IMTC/94. Advanced Technologies in I & M. 1994 IEEE Instrumentation and Measurement Technolgy Conference (Cat. No.94CH3424-9).