Automatic defect inspection system of colour filters using Taguchi-based neural network

International Journal of Production Research

Volumn 51, Issue 5, 2013, Pages 1464-1476

  Kuo, Chung Feng ^a   Hsu, Chien Tung Max ^a   Fang, Chih Heng ^a   Chao, Shin Min ^b   Lin, Yu De ^a  

^a NATIONAL TAIWAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Taiwan)

^b BenQ Materials Corporation   (Taiwan)

Author keywords

Automatic defect inspection; Colour filter; Image processing; LCD panel; Neural network; Taguchi method

Indexed keywords

AUTOMATIC DEFECT INSPECTION; BACK-PROPAGATION NEURAL NETWORKS; CRITICAL PARTS; DEFECT DETECTION; DETECTION EFFICIENCY; DETECTION ERROR; FASTER CONVERGENCE; HIGH QUALITY; IMAGE PROCESSING TECHNOLOGY; LCD PANELS; LEARNING PARAMETERS; MANUAL INSPECTION; MICRO-DEFECTS; PRODUCTION COST; RECOGNITION RATES; ROOT-MEAN-SQUARE ERRORS; TRIAL-AND-ERROR METHOD;

DEFECTS; ERRORS; IMAGE PROCESSING; INSPECTION; LIQUID CRYSTAL DISPLAYS; NEURAL NETWORKS; TAGUCHI METHODS;

COLOR;

EID: 84871236504     PISSN: 00207543     EISSN: 1366588X     Source Type: Journal    
DOI: 10.1080/00207543.2012.695877     Document Type: Article

References (21)

1. Bachlaus, M., Tiwari, M.K., and Chan, F.T.S., 2009. Multi-objective resource assignment problem in a product-driven supply chain using a Taguchi-based DNA algorithm. International Journal of Production Research, 47 (9), 2345-2371.
2. Castellani, M. and Rowlands, H., 2008. Evolutionary feature selection applied to artificial neural networks for wood-veneer classification. International Journal of Production Research, 46 (11), 3085-3105.
3. Chang, C.L., Chang, H.H. and Hsu, C.P., 2005. An intelligent defect inspection technique for colour filter. Proceedings of the 2005 IEEE International Conference on Mechatronics, 10-12 July, Taipei, Taiwan, 1529388, pp. 933-944.
4. Hostis, P.L., Byers, F., Podio, F. and Tang, X., 1999. Microscopic image analysis of defect areas in optical disks. Proceedings of SPIE - The International Society for Optical Engineering, 3806, 106-112.
5. Hwarng, H.B., 2004. Detecting process mean shift in the presence of autocorrelation: a neural-network based monitoring scheme. International Journal of Production Research, 42 (3), 573-595.
6. Hwarng, H.B., 2005. Simultaneous identification of mean shift and correlation change in AR(1) processes. International Journal of Production Research, 43 (9), 1761-1783.
7. Hwarng, H.B., 2008. Toward identifying the source of mean shifts in multivariate SPC: a neural network approach. International Journal of Production Research, 46 (20), 5531-5559.
8. Jiang, B.C. and Jiang, S.J., 1998. Machine vision based inspection of oil seals. Journal of Manufacturing Systems, 17 (3), 159-166.
9. Jiang, B.C., Tsai, S.L., and Wang, C.C., 2002. Machine vision-based grey relational theory applied to IC marking inspection. IEEE Transactions on Semiconductor Manufacturing, 15 (4), 531-539.
10. Kuo, C.-.F.J. and Su, T.L., 2006. Optimisation of multiple quality characteristics for polyether ketone injection molding process. Fibers and Polymers, 7 (4), 404-413.
11. Kuo, C.-.F.J., Su, T.L., and Tsai, C.P., 2007. Optimisation of the needle punching process for the non-woven fabrics with multiple quality characteristics by grey-based Taguchi method. Fibers and Polymers, 8 (6), 654-664.
12. Lee, C.L. and Chen, S.Y., 2006. Classification of leaf images. International Journal of Imaging Systems and Technology, 16 (1), 15-23.
13. Lu, C.J. and Tsai, D.M., 2004. Defect inspection of patterned thin film transistor-liquid crystal display panels using a fast sub-image-based singular value decomposition. International Journal of Production Research, 42 (20), 4331-4351.
14. Otsu, N., 1979. A threshold selection method from gray-level histograms. IEEE Transactions on Systems, Man, and Cybernetics, 9 (1), 62-66.
15. Perng, D.B., Chen, S.H., and Chang, Y.S., 2010. A novel internal thread defect auto-inspection system. International Journal of Advanced Manufacturing Technology, 47 (5-8), 731-743.
16. Rumelhart, D. and McClelland, J., 1986. Parallel Distributed Processing. Cambridge, Mass: MIT Press.
17. Su, C.T., Yang, T., and Ke, C.M., 2002. A neural network approach for semiconductor wafer post-sawing inspection. IEEE Transactions on Semiconductor Manufacturing, 15 (2), 260-266.
18. Tsai, D.M. and Hsieh, C.Y., 1999. Automated surface inspection for directional textures. Image and Vision Computing, 18 (1), 49-62.
19. Tsai, D.M. and Chiang, C.H., 2003. Automatic band selection for wavelet reconstruction in the application of defect detection. Image and Vision Computing, 21 (5), 413-431.
20. Tsai, D.M., Lin, P.C., and Lu, C.J., 2006. An independent component analysis based filter design for defect detection in low-contrast surface images. Pattern Recognition, 39 (9), 1679-1694.
21. Wu, M.H., Fuh, C.S., and Chen, H.Y., 2000. Defect inspection and analysis of colour filter panel. Image and Recognition, 6 (2), 74-90.