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Proceedings Paper

Pattern recognition with adaptive nonlinear filters
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Paper Abstract

In this paper, adaptive nonlinear correlation-based filters for pattern recognition are presented. The filters are based on a sum of minima correlations. To improve the recognition performance of the filters in presence of false objects and geometric distortions, information about the objects is used to synthesize the filters. The performance of the proposed filters is compared to that of the linear synthetic discriminant function filters in terms of noise robustness and discrimination capability. Computer simulation results are provided and discussed.

Paper Details

Date Published: 24 September 2007
PDF: 7 pages
Proc. SPIE 6696, Applications of Digital Image Processing XXX, 66961Z (24 September 2007); doi: 10.1117/12.734240
Show Author Affiliations
Saúl Martínez-Díaz, 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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