Multi-objective adaptive composite filters for object recognition

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

Research output: Contribution to conferencePaper

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. © 2011 SPIE.
Original languageAmerican English
DOIs
StatePublished - 1 Nov 2011
Externally publishedYes
EventProceedings of SPIE - The International Society for Optical Engineering -
Duration: 1 Jan 2015 → …

Conference

ConferenceProceedings of SPIE - The International Society for Optical Engineering
Period1/01/15 → …

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Armenta-Nieblas, J. L., Diaz-Ramirez, V. H., & Tapia-Armenta, J. J. (2011). Multi-objective adaptive composite filters for object recognition. Paper presented at Proceedings of SPIE - The International Society for Optical Engineering, . https://doi.org/10.1117/12.894354