An intelligent defect inspection technique for color filter

Automatic defect inspection systems are becoming more and more important in industrial production lines. Especially in electronics industry, an attempt is often made to achieve almost 100% quality control of all components and final goods. Here we are interested in the defect inspection of color filter, which is one of components in TFT-LCD module and gives each pixel of LCD its own color. The difficulties in the defect inspection of color filter are its complex texture and demand for high-speed processing. In this paper, we propose a neural-fuzzy-inference-network (NFIN)-based defect inspection algorithm to detect the materials with regular pattern such as color filter. The NFIN, which is basically a fuzzy inference system and its fuzzy rules and corresponding parameters can be learned by neural network automatically, is a good alternative to achieve the defect inspection. Experimental results show that the proposed algorithm is a promising method to detect the defects of color filter. The proposed algorithm can apply to not only the detection of color filter but also the detection of web materials.

[1]  Michael J. Swain,et al.  Indexing via color histograms , 1990, [1990] Proceedings Third International Conference on Computer Vision.

[2]  Takashi Kido IN-PROCESS INSPECTION TECHNIQUE FOR ACTIVE-MATRIX LCD PANELS , 1992, Proceedings International Test Conference 1992.

[3]  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).

[4]  Hiroshi Murase,et al.  Fast visual search using focused color matching—active search , 2000 .

[5]  C.-S. Lin,et al.  Using discriminate function and counting mask operation for counting spacers in liquid crystals display plate , 1998 .

[6]  Thong-Shing Hwang,et al.  The preprocessing and recognition methods of an integrated automated production lot number inspection system , 2003 .

[7]  Michael J. Swain,et al.  Color indexing , 1991, International Journal of Computer Vision.