Adaptive Bayesian approach for color image segmentation

Michael M. Chang; Andrew J. Patti; M. Ibrahim Sezan; A. Murat Tekalp

doi:10.1117/12.157998

22 October 1993 Adaptive Bayesian approach for color image segmentation

Michael M. Chang, Andrew J. Patti, M. Ibrahim Sezan, A. Murat Tekalp

Proceedings Volume 2094, Visual Communications and Image Processing '93; (1993) https://doi.org/10.1117/12.157998
Event: Visual Communications and Image Processing '93, 1993, Cambridge, MA, United States

Abstract

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.

Citation Download Citation

Michael M. Chang, Andrew J. Patti, M. Ibrahim Sezan, and A. Murat Tekalp "Adaptive Bayesian approach for color image segmentation", Proc. SPIE 2094, Visual Communications and Image Processing '93, (22 October 1993); https://doi.org/10.1117/12.157998

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