EM algorithms for Gaussian mixtures with split-and-merge operation

被引:103
作者
Zhang, ZH
Chen, CB
Sun, J
Chan, KL
机构
[1] Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore 639798, Singapore
[2] Beijing Sigma Ctr, MSR, Microsoft Res Asia, Beijing 100080, Peoples R China
关键词
Gaussian mixtures; EM algorithms; split-and-merge operation; statistical computer vision; image segmentation;
D O I
10.1016/S0031-3203(03)00059-1
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In order to alleviate the problem of local convergence of the usual EM algorithm, a split-and-merge operation is introduced into the EM algorithm for Gaussian mixtures. The split-and-merge equations are first presented theoretically. These equations show that the merge operation is a well-posed problem, whereas the split operation is an ill-posed problem because it is the inverse procedure of the merge. Two methods for solving this ill-posed problem are developed through the singular value decomposition and the Cholesky decomposition. Accordingly, a new modified EM algorithm is constructed. Our experiments demonstrate that this algorithm is efficient for unsupervised color image segmentation. (C) 2003 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.
引用
收藏
页码:1973 / 1983
页数:11
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