文章基本信息

标题：Unsupervised Image Segmentation Based on Bethe Approximation
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作者：Fan CHEN ; Takafumi AOKI ; Tsuyoshi HORIGUCHI 等
期刊名称：Interdisciplinary Information Sciences
印刷版ISSN：1340-9050
电子版ISSN：1347-6157
出版年度：2005
卷号：11
期号：2
页码：127-139
DOI：10.4036/iis.2005.127
出版社：The Editorial Committee of the Interdisciplinary Information Sciences
摘要：We propose an approach for unsupervised image segmentation based on the Markov random field by using the Bethe approximation. We first derive the Bayesian information criterion under the Bethe approximation and then propose an iterative algorithm to search a model which fits the image data best. For this aim, we derive a criterion for merging two components among several components in terms of a perturbation expansion. Namely, annihilation of components is implemented by merging two components into one component after each convergence of the supervised segmentation with a fixed number of components. We find by numerical experiments that the optimal number of components is selected from the series of local optima with different numbers of components and the best result for segmentation is obtained with good performance.
关键词：unsupervised image segmentation;Bethe approximation;EM algorithm;component annihilation;perturbation expansion