Bayesian classification validation scheme driven by a localized/low-resolution Bhattacharyya distance classifier
Emerson P. Lopes · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1999
A scheme for comparative performance analysis of the Bayesian and the Bhattacharyya distance RCE neural network classifiers is presented. The experiments are performed on synthetic and Brodatz textures. The introduction of the new classifier aims at obtaining a better performance in classifying non-stationary multi-texture images. The two classification schemes are assessed on their localized data representation regarding the ability of extracting non- stationary information from the image. Low-resolution data representation is used to reduce the instability produced with the search for a better trade-off between accuracy and spatial classification performances.