%0 Journal Article
%A HUANG Chenxue
%A WANG Lei
%T Improved hierarchical Markov random field algorithm color image segmentation algorithm
%D 2016
%R 10.11772/j.issn.1001-9081.2016.09.2576
%J Journal of Computer Applications
%P 2576-2579
%V 36
%N 9
%X The distribution of color image pixel value is difficult to describe in hierarchical Markov Random Field (MRF) segmentation algorithm, therefore, a hierarchical MRF segmentation algorithm based on RGB color statistic distribution was proposed to solve this problem. The key parameters of the MRF model were set up, and the related formulas were deduced. With the RGB color statistic distribution model, the hierarchical MRF energy function was rewritten, and the *k*-means algorithm was used as presegmentation method to realize unsupervised segmentation. The proposed algorithm has fewer color distribution parameters and lower computational cost in comparison with traditional MRF segmentation model, which describes color distribution more accurately; and it can describe different targets and background very well without being restricted by target and background color distribution and target spatial distribution. Experimental results prove the effectiveness of the proposed algorithm, which is superior to the MRF algorithm and Fuzzy C-Means (FCM) algorithm in computing speed and segmentation accuracy.
%U http://www.joca.cn/EN/10.11772/j.issn.1001-9081.2016.09.2576