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Optical Engineering

Nonlinear synthetic discriminant function filters for illumination-invariant pattern recognition
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Paper Abstract

Novel nonlinear adaptive composite filters for illumination-invariant pattern recognition are presented. Pattern recognition is carried out with space-variant nonlinear correlation. The information about objects to be recognized, false objects, and a background to be rejected is utilized in an iterative training procedure to design a nonlinear adaptive correlation filter with a given discrimination capability. The designed filter during recognition process adapts its parameters to local statistics of the input image. Computer simulation results obtained with the proposed filters in nonuniformly illuminated test scenes are discussed and compared with those of linear composite correlation filters with respect to discrimination capability, robustness to input additive and impulsive noise, and tolerance to small geometric image distortions.

Paper Details

Date Published: 1 June 2008
PDF: 4 pages
Opt. Eng. 47(6) 067201 doi: 10.1117/1.2940371
Published in: Optical Engineering Volume 47, Issue 6
Show Author Affiliations
Saul Martinez-Diaz, 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)


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