Pattern recognition with adaptive nonlinear filters

Saúl Martínez-Díaz; Vitaly Kober

doi:10.1117/12.734240

24 September 2007 Pattern recognition with adaptive nonlinear filters

Saúl Martínez-Díaz, Vitaly Kober

Proceedings Volume 6696, Applications of Digital Image Processing XXX; 66961Z (2007) https://doi.org/10.1117/12.734240
Event: Optical Engineering + Applications, 2007, San Diego, California, United States

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.

Citation Download Citation

Saúl Martínez-Díaz and Vitaly Kober "Pattern recognition with adaptive nonlinear filters", Proc. SPIE 6696, Applications of Digital Image Processing XXX, 66961Z (24 September 2007); https://doi.org/10.1117/12.734240

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