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http://dx.doi.org/10.5391/JKIIS.2015.25.6.523

Incremental EM algorithm with multiresolution kd-trees and cluster validation and its application to image segmentation  

Lee, Kyoung-Mi (Department of Computer Science, Duksung Women's University)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.25, no.6, 2015 , pp. 523-528 More about this Journal
Abstract
In this paper, we propose a new multiresolutional and dynamic approach of the EM algorithm. EM is a very popular and powerful clustering algorithm. EM, however, has problems that indexes multiresolution data and requires a priori information on a proper number of clusters in many applications, To solve such problems, the proposed EM algorithm can impose a multiresolution kd-tree structure in the E-step and allocates a cluster based on sequential data. To validate clusters, we use a merge criteria for cluster merging. We demonstrate the proposed EM algorithm outperforms for texture image segmentation.
Keywords
Clustering; EM Algorithm; Kd-tree; Cluster Validate; Image Segmentation;
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Times Cited By KSCI : 2  (Citation Analysis)
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