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Proceedings Paper

Pattern recognition with an adaptive generalized SDF filter
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Paper Abstract

Most of captured images present degradations due to blurring and additive noise; moreover objects of interest can be geometrically distorted. The classical methods for pattern recognition based on correlation are very sensitive to intensity degradations and geometric distortions. In this work, we propose an adaptive generalized filter based on synthetic discriminant function (SDF). With the help of computer simulation we analyze and compare the performance of the adaptive correlation filter with that of common correlation filters in terms of discrimination capability and accuracy of target location when input scenes are degraded and a target is geometrically distorted.

Paper Details

Date Published: 24 September 2007
PDF: 7 pages
Proc. SPIE 6696, Applications of Digital Image Processing XXX, 66961V (24 September 2007); doi: 10.1117/12.732554
Show Author Affiliations
E. M. Ramos-Michel, CICESE (Mexico)
Vitaly Kober, CICESE (Mexico)


Published in SPIE Proceedings Vol. 6696:
Applications of Digital Image Processing XXX
Andrew G. Tescher, Editor(s)

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