DocumentCode
1990271
Title
Estimation of Markov Random Field Parameters Using Ant Colony Optimization for Continuous Domains
Author
Yu, Yihua
Author_Institution
Sch. of Sci., Beijing Univ. of Posts & Telecommun., Beijing, China
fYear
2012
fDate
27-30 May 2012
Firstpage
1
Lastpage
4
Abstract
In this paper, we present a method based on ant colony optimization for continuous domains (ACOC) to estimate the Markov random field parameters, using the maximum likelihood criterion. In order to model the multi-level image patterns more accurately, we define a new clique potential function. Experimental results and performance comparison with the Markov chain Monte Carlo method are provided to illustrate the performance of the ACOC-based method.
Keywords
Markov processes; ant colony optimisation; image segmentation; maximum likelihood estimation; ACOC; Markov random field parameter; ant colony optimization for continuous domain; clique potential function; maximum likelihood criterion; multilevel image pattern; Ant colony optimization; Markov random fields; Maximum likelihood estimation; Monte Carlo methods; Parameter estimation;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering and Technology (S-CET), 2012 Spring Congress on
Conference_Location
Xian
Print_ISBN
978-1-4577-1965-3
Type
conf
DOI
10.1109/SCET.2012.6342010
Filename
6342010
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