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 language||American English|
|State||Published - 1 Nov 2011|
|Event||Proceedings of SPIE - The International Society for Optical Engineering - |
Duration: 1 Jan 2015 → …
|Conference||Proceedings of SPIE - The International Society for Optical Engineering|
|Period||1/01/15 → …|
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