1 June 2008 Nonlinear synthetic discriminant function filters for illumination-invariant pattern recognition
Author Affiliations +
Optical Engineering, 47(6), 067201 (2008). doi:10.1117/1.2940371
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.
Saul Martinez-Diaz, Vitaly I. Kober, "Nonlinear synthetic discriminant function filters for illumination-invariant pattern recognition," Optical Engineering 47(6), 067201 (1 June 2008). http://dx.doi.org/10.1117/1.2940371
JOURNAL ARTICLE
4 PAGES


SHARE
KEYWORDS
Nonlinear filtering

Image filtering

Composites

Nonlinear dynamics

Optical filters

Linear filtering

Digital filtering

Back to Top