DocumentCode :
1705119
Title :
The Ising/Potts model is not well suited to segmentation tasks
Author :
Morris, R.D. ; Descombes, X. ; Zerubia, J.
Author_Institution :
INRIA, Sophia Antipolis, France
fYear :
1996
Firstpage :
263
Lastpage :
266
Abstract :
The Ising and Potts models have been used since the earliest work on Markov random fields (MRF) based image segmentation as the underlying model for the region labels, and continue to be used for this task. However, advances in Markov chain Monte Carlo techniques have highlighted the shortcomings of these models as models of region labels. We present a demonstration of why these models are unsuitable for segmentation. We hope this will help motivate the search for better models
Keywords :
Markov processes; Monte Carlo methods; Potts model; image segmentation; random processes; statistical analysis; Ising/Potts model; MRF; Markov chain Monte Carlo techniques; image segmentation; region labels; statistical physics; Conferences; Digital signal processing; Image sampling; Image segmentation; Markov random fields; Parameter estimation; Pixel; Shape; Smoothing methods; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Digital Signal Processing Workshop Proceedings, 1996., IEEE
Conference_Location :
Loen
Print_ISBN :
0-7803-3629-1
Type :
conf
DOI :
10.1109/DSPWS.1996.555511
Filename :
555511
Link To Document :
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