所属单位：

信息与控制工程学院

发表刊物：

2010 International Conference on Electrical and Control Engineering

关键字：

中文关键字：图像分割；马尔可夫随机场；GBP算法，英文关键字：Image segmentation; GBP algorithm; EM algorithm; G

摘要：

Belief propagation (BP) algorithm is an efficient way for image segmentation based on graphical models. However BP fails to converge when the graph has cycles. Generalized belief propagation (GBP) provides more accurate solutions on such graphs. In this paper, a method based on GBP algorithm is proposed for image segmentation. In proposed method, class label is modeled using Gaussian Markov random fields (GMRF), and expectation maximization (EM) algorithm was adopted to estimate the hyper-parameters of GMRF. After region graph constructed, we run GBP algorithm on region graph, to maximize the posteriori conditional probability distribution based on Bayesian theory. The analysis and experiments on natural images showed that it gives much more accurate results than those found using ordinary belief propagation

备注：

徐胜军

合写作者：

张熹

第一作者：

徐胜军

论文类型：

期刊论文

卷号：

卷：

期号：

期：

页面范围：

页：1158

是否译文：

否

发表时间：

2010-06-01