Browse > Article
http://dx.doi.org/10.6109/jkiice.2013.17.8.1899

COF Defect Detection and Classification System Based on Reference Image  

Kim, Jin-Soo (Department of Information and Communication Engineering, Hanbat National University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.17, no.8, 2013 , pp. 1899-1907 More about this Journal
Abstract
This paper presents an efficient defect detection and classification system based on reference image for COF (Chip-on-Film) which encounters fatal defects after ultra fine pattern fabrication. These defects include typical ones such as open, mouse bite (near open), hard short and soft short. In order to detect these defects, conventionally it needs visual examination or electric circuits. However, these methods requires huge amount of time and money. In this paper, based on reference image, the proposed system detects fatal defect and efficiently classifies it to one of 4 types. The proposed system includes the preprocessing of the test image, the extraction of ROI, the analysis of local binary pattern and classification. Through simulations with lots of sample images, it is shown that the proposed system is very efficient in reducing huge amount of time and money for detecting the defects of ultra fine pattern COF.
Keywords
Chip-on-Film; Defect detection; Reference image;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Y. -T. Hsieh, "Reliability and Failure Mode of Chip-onfilm with Non-conductive Adhesive", IEEE Proceedings of the 4th Int. Symposium on Electronic Materials and Packaging, pp. 157-160, Dec. 4-6, Taiwan, 2002.
2 G.Zhao, M.Pietikainen "Dynamic Texture Recognition Using Local Binary Patterns with an Application to Facial Expressions", IEEE Tr. on PAMI, 2007, pp1.-14.
3 Y.W. Cha, H.W. Kim, S.I.Yoo, "Reference Image-Based Defect Detection Using Shape Analysis", IPIU 2010, Jan. 2010
4 O. Boiman, M. Irani, "Detecting Irregularities in Images and Video," International Journal of Computer Vision, vol.74, no.1, pp.17-31, Jan., 2007.   DOI   ScienceOn
5 K. Taniguchi, S. Tatsumi, "A Detection Method for Irregular Lightness Variation of Low Contrast", IEEE International Conference on Systems, Man and Cybernetics, vol. 7, pp. 6401-6406, 2004.
6 Y.S. Kim et al, "Defects Detection of TCP/COF Using Real-Time Line Scanner", CICS'07, pp.153-154, Oct. 2007.
7 J.-Y. Ryu, "Development of Automatic System for Fault Detection of Fine Pitch Chip-on-Films", The Journal of Korean Institute of Information, vol.9, no.1, pp. 25-34, Jan. 2011.
8 D.-W. Choi, J.-Y. Ryu, "Defect Detection System for Ultra Fine Pattern Chip-on-Film", The Journal of Korean Institute of Information, vol. 9, no.5, pp. 1-8, May 2011.
9 J. Lee, S. Yoo, "Detection of Defects on Repeated Multi-Patterned Image," Journal of KIISE : Software and Applications, vol.37, no.5, May 2010.
10 S. -M. Chang, J. -H. Jou, A. Hsieh, T. -H. Chen, C. -Y. Chang, Y. -H. Wang, and C. -M. Huang, "Characteristic Study of Anisotropic-conductive Film for Chip-on-film Packaging", icroelectronics Reliability, Vol. 41, No. 12, pp. 2001-2009, Dec. 2001.   DOI   ScienceOn
11 Moganti. M, Ercal. F, "Automatic PCB Inspection Systems," IEEE Potentials, Vol. 14, Issue:3, pp. 6-10, 1995.
12 D. M. Tsai and C. P. Lin, "Fast Defect Detection in Textured Surface Using 1D Gabor Filter," Int. Journal of Advanced Manufacturing Technology, Vol. 20, pp. 664-675, 2003
13 J. Chen and A. K. Jain, "A Structural Approach to Identify Defects on Textural Image," Proc. of IEEE Int. Con. on Systems, Man., and Cybernetics, pp. 29-32, 1998
14 I. S. Jeong and O. J. Kwon, "Real-time PCB Vision Inspection Using Pattern Matchings", Proc. of IEEK Summer Conference, Vol. 26, No. 1, pp. 2335-2338, 2003.