EM algorithms for Gaussian mixtures with split-and-merge operation
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 prob...
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Published in | Pattern recognition Vol. 36; no. 9; pp. 1973 - 1983 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Elsevier Ltd
01.09.2003
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Subjects | |
Online Access | Get full text |
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Summary: | 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. |
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ISSN: | 0031-3203 1873-5142 |
DOI: | 10.1016/S0031-3203(03)00059-1 |