Title :
Estimation of Markov Random Field Parameters Using Ant Colony Optimization for Continuous Domains
Author_Institution :
Sch. of Sci., Beijing Univ. of Posts & Telecommun., Beijing, China
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;
Conference_Titel :
Engineering and Technology (S-CET), 2012 Spring Congress on
Conference_Location :
Xian
Print_ISBN :
978-1-4577-1965-3
DOI :
10.1109/SCET.2012.6342010
