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Optical Engineering

Adaptive synthetic discriminant function filters for pattern recognition
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Paper 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.

Paper Details

Date Published: 1 May 2006
PDF: 10 pages
Opt. Eng. 45(5) 057005 doi: 10.1117/1.2205232
Published in: Optical Engineering Volume 45, Issue 5
Show Author Affiliations
Angel J. González-Fraga, Ctr. de Investigación Científica y de Educación Superior de Ensenada (Mexico)
Vitaly I. Kober, Ctr. de Investigación Científica y de Educación Superior de Ensenada (Mexico)
Josué Álvarez-Borrego, Ctr. de Investigación Científica y de Educación Superior de Ensenada (Mexico)


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