Distortion-invariant pattern recognition with nonlinear correlation filters

Saúl Martínez-Díaz; Vitaly Kober

doi:10.1117/12.795546

15 September 2008 Distortion-invariant pattern recognition with nonlinear correlation filters

Saúl Martínez-Díaz, Vitaly Kober

Proceedings Volume 7073, Applications of Digital Image Processing XXXI; 707327 (2008) https://doi.org/10.1117/12.795546
Event: Optical Engineering + Applications, 2008, San Diego, California, United States

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.

Citation Download Citation

Saúl Martínez-Díaz and Vitaly Kober "Distortion-invariant pattern recognition with nonlinear correlation filters", Proc. SPIE 7073, Applications of Digital Image Processing XXXI, 707327 (15 September 2008); https://doi.org/10.1117/12.795546

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