Adaptive Bayesian approach for color image segmentation
Michael Ming Yuen Chang, Andrew J. Patti, M. Ibrahim Sezan, Ahmet Murat Tekalp · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1993
A Bayesian segmentation algorithm to separate color images into regions of distinct colors is presented. The algorithm takes into account the local color variations in the image in an adaptive manner. A Gibbs random field (GRF) is used as the a priori probability model for the segmentation process to impose a spatial connectivity constraint. We study the performance of the proposed algorithm in different color spaces and its application in reduced data rendering of color images. Experimental results and discussion are included.