Multi-objective adaptive composite filters for object recognition

Jose L. Armenta-Nieblas; Victor H. Diaz-Ramirez; Juan J. Tapia-Armenta

doi:10.1117/12.894354

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12 September 2011 Multi-objective adaptive composite filters for object recognition

Jose L. Armenta-Nieblas, Victor H. Diaz-Ramirez, Juan J. Tapia-Armenta

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Proceedings Volume 8134, Optics and Photonics for Information Processing V; 813404 (2011) https://doi.org/10.1117/12.894354
Event: SPIE Optical Engineering + Applications, 2011, San Diego, California, United States

Abstract

An iterative algorithm to design optimal trade-off correlation filters for pattern recognition is presented. The algorithm is based on a heuristic optimization of several conflicting metrics simultaneously. By the use of the heuristic algorithm the impulse response of a conventional composite filter is iteratively synthesized until an optimal trade-off of the considered quality metrics is obtained. Computer simulation results obtained with the proposed filters are provided and analyzed in terms of recognition quality measures in cluttered, and geometrically distorted input test scenes.

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Jose L. Armenta-Nieblas, Victor H. Diaz-Ramirez, and Juan J. Tapia-Armenta "Multi-objective adaptive composite filters for object recognition", Proc. SPIE 8134, Optics and Photonics for Information Processing V, 813404 (12 September 2011); https://doi.org/10.1117/12.894354

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