Adaptive synthetic discriminant function filters for pattern recognition

Angel J. González-Fraga; Vitaly I. Kober; Josué Álvarez-Borrego

doi:10.1117/1.2205232

1 May 2006 Adaptive synthetic discriminant function filters for pattern recognition

Angel J. González-Fraga, Vitaly I. Kober, Josué Álvarez-Borrego

Author Affiliations +

Optical Engineering, Vol. 45, Issue 5, 057005 (May 2006). https://doi.org/10.1117/1.2205232

Abstract

New adaptive correlation filters based on a conventional synthetic discriminant function (SDF) for reliable recognition of an object in cluttered background are proposed. The information about an object to be recognized, false objects, and a background to be rejected is utilized in an iterative training procedure to design a correlation filter with a given value of discrimination capability. Computer simulation results obtained with the proposed adaptive filter in test scenes are discussed and compared with those of various correlation filters in terms of discrimination capability, tolerance to input additive noise that is always present in image sensors, and to small geometric image distortions.

©(2006) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

Angel J. González-Fraga, Vitaly I. Kober, and Josué Álvarez-Borrego "Adaptive synthetic discriminant function filters for pattern recognition," Optical Engineering 45(5), 057005 (1 May 2006). https://doi.org/10.1117/1.2205232

Published: 1 May 2006

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