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Adaptive color image segmentation using Markov random fields

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2 Author(s)
Wesolkowski, S. ; Syst. Design Eng., Waterloo Univ., Ont., Canada ; Fieguth, P.

A new framework for color image segmentation is introduced generalizing the concepts of point-based and spatially-based methods. This framework is based on Markov random fields using a continuous Gibbs sampler. The Markov random fields approach allows for a rigorous computational framework where local and global spatial constraints can be globally optimized. Using a continuous Gibbs sampler enables the algorithm to adapt continuous-valued regional prototypes in a manner analogous to vector quantization while the discrete Gibbs sampler is used to adjust region boundaries.

Published in:

Image Processing. 2002. Proceedings. 2002 International Conference on  (Volume:3 )

Date of Conference:

24-28 June 2002