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Proceedings Paper

Distortion-invariant pattern recognition with nonlinear correlation filters
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Paper Abstract

Classical correlation-based methods for pattern recognition are very sensitive to geometrical distortions of objects to be recognized. Besides, most captured images are corrupted by noise. In this work we use novel nonlinear composite filters for distortion-invariant pattern recognition. The filters are designed with an iterative algorithm to reject a background noise and to achieve a desired discrimination capability. The recognition performance of the proposed filters is compared with that of linear composite filters in terms of noise robustness and discrimination capability. Computer simulation results are provided and discussed.

Paper Details

Date Published: 15 September 2008
PDF: 8 pages
Proc. SPIE 7073, Applications of Digital Image Processing XXXI, 707327 (15 September 2008); doi: 10.1117/12.795546
Show Author Affiliations
Saúl Martínez-Díaz, CISESE (Mexico)
Vitaly Kober, CISESE (Mexico)


Published in SPIE Proceedings Vol. 7073:
Applications of Digital Image Processing XXXI
Andrew G. Tescher, Editor(s)

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