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http://dx.doi.org/10.3745/KIPSTB.2004.11B.3.327

Development of an Edge-based Point Correlation Algorithm Avoiding Full Point Search in Visual Inspection System  

Kang, Dong-Joong (동명정보대학교 메카트로닉스공학과)
Kim, Mun-Jo (한국정보통신대학원대학교 공학)
Kim, Min-Sung (동명정보대학교 정보통신학)
Lee, Eung-Joo (동명정보대학교 정보통신학과)
Abstract
For visual inspection system in real industrial environment, it is one of most important tasks to design fast and stable pattern matching algorithm. This paper presents an edge-based point correlation algorithm avoiding full search in visual inspection system. Conventional algorithms based on NGC(normalized gray-level correlation) have to overcome some difficulties for applying to automated inspection system in factory environment. First of all, NGC algorithms need high time complexity and thus high performance hardware to satisfy real-time process. In addition, lighting condition in realistic factory environments if not stable and therefore intensity variation from uncontrolled lights gives many roubles for applying directly NGC as pattern matching algorithm in this paper, we propose an algorithm to solve these problems from using thinned and binarized edge data and skipping full point search with edge-map analysis. A point correlation algorithm with the thinned edges is introduced with image pyramid technique to reduce the time complexity. Matching edges instead of using original gray-level pixel data overcomes NGC problems and pyramid of edges also provides fast and stable processing. All proposed methods are preyed from experiments using real images.
Keywords
Visual Inspection; NGC; Point Correlation; Edges; Skipping Full Search; Image Pyramid;
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  • Reference
1 W. Krattenthaler, K. J. Mayer, M. Zeiller, 'POINT CORRELATION: A Reduced-Cost Template Matching Technique,' IEEE Int. Conf. on Image Processing, pp.208-212, 1994   DOI
2 S. Manickam, S. D. Roth, T. Bushman, 'Intelligent and Optimal Normalized Correlation for High-Speed Pattern Matching, Datacube Technical Paper,' Datacube Incorpolation, 2000
3 Searches, model, and model search parameters, Matrox User Manual, Matrox Incorpolation, pp.135-158, 1998
4 A. Rosenfeld and A. C. Kak, 'Digital picture processing,' Academic Press, New York, 1976
5 S. S. Gleason, M. A. Hunt, and W. B. Jatko, 'Subpixel measurement of image features based on paraboloid surface fit,' SPIE V. 1386, Machine Vision Systems Integration in Industry, 1990   DOI
6 J. Canny, 'A Computational approach to edge detection,' IEEE Trans. Pattern Analysis and Machine Intelligence, Vol.8, No.6, 1986   DOI   ScienceOn
7 D. J. Kang and I. S. Kweon, 'An-edge based algorithm for discontinuity adaptive color image smoothing,' Pattern Recognition, Vol.34, No.2, pp.333-342, 2001   DOI   ScienceOn