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http://dx.doi.org/10.6109/jkiice.2007.11.3.577

A Mark Automatic Checking System to Inspect Character String on Chip  

Kim, Eun-Seok (아주대학교 산업공학과)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.11, no.3, 2007 , pp. 577-583 More about this Journal
Abstract
The character strings on chips and components are so tiny and numerous that it is a very difficult work for people to perform. In this paper, we propose a mark automatic checking system, which will determine whether chip is wrong-mark or not by recognizing characters on chips. Lots of faulty detection conditions and template matching methods are used to inspect the faulty mark items. The faulty detection classifies conditions as five kinds-darkness, matching, area, broken and branch. A series of experimentation show that the method proposed here can offer an effective way to determine wrong-mark on chips.
Keywords
mark; template matching; broken; branch;
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1 Zheng, Z., Wang, H. and Teoh, K., 'Analysis of gray level corner detection,' Pattern Recognition Letters, vol.20, pp. 149-162, 1999   DOI   ScienceOn
2 Jie Yang, Hua Yu, 'A Direct LDA Algorithm for High-Dimensional Data with Application to Face Recognition.' Pattern Recognition 34(10), pp. 2067-2070, 2001   DOI   ScienceOn
3 Soon H. Kwon, 'Threshold selection based on cluster analysis', Pattern Recognition Letters, Vol 25, Issue 9, pp. 1045-1050, 2 July 2004   DOI   ScienceOn
4 A. Roddy and J. Stosz, 'Fingerprint Features: Statistical Analysis and System Performance Estimates,' Proc. of IEEE, Vol. 85, No.9, pp. 1390-1421, 1997   DOI   ScienceOn
5 Gatos B., Pratikakis I. and Perantonis S.J., 'An Adaptive Binarization Technique for Low Quality Historical Documents', IAPR workshop on document analysis systems(DAS2004), Lecture Notes in Computer Science(3163), Florence, Italy, pp. 102-113
6 Zhiyan Wang, Yunjie Li, and Zhimin Luo, 'An Automatic Chip Character Checking System for Circuit Board Quality Control', Industrial Electronics Society, 2003. IECON '03. The 29th Annual Conference of the IEEE Vol. 2, pp. 1767-1770, 2003
7 Jeong, S. W., Kim, S. H. and Cho, W. H., 'Performance comparison of statistical and neural network classifiers in hand-written digits recognition,' Proc. 6th IWFHR, Taejon, pp. 419-428, 1998
8 L. S. Oliveira, R. Sabourin, F. Bortolozzi, and C. Y. Suen, 'Automatic recognition of handwritten numerical strings: A recognition and verification strategy,' IEEE Trans. on PAMI, vol. 24, no. 11, pp. 1438-1454, 2002   DOI   ScienceOn