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

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