1 June 2008 Nonlinear synthetic discriminant function filters for illumination-invariant pattern recognition
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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.
© (2008) Society of Photo-Optical Instrumentation Engineers (SPIE)
Saul Martinez-Diaz, Saul Martinez-Diaz, Vitaly I. Kober, Vitaly I. Kober, } "Nonlinear synthetic discriminant function filters for illumination-invariant pattern recognition," Optical Engineering 47(6), 067201 (1 June 2008). https://doi.org/10.1117/1.2940371 . Submission:
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