We describe an approach to compute filters that automatically performs a spatial frequency selection to improve interclass discrimination and to reduce intraclass sensitivity. This approach is achieved by using as input to the filter synthesis a set of reference images to compute the filters and a set of distorted images to introduce the distortion or noise model of the reference images. Simulation results of correlation examples are provided for two pattern-recognition problems and are compared with the ones obtained with the standard minimum average correlation energy filters.
© 1993 Optical Society of America
Original Manuscript: June 26, 1992
Published: August 10, 1993
Frank Dubois, "Automatic spatial frequency selection algorithm for pattern recognition by correlation," Appl. Opt. 32, 4365-4371 (1993)