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ABSTRACT
<p><b>Abstract</b>—In this paper, we propose a modified version of the K-means algorithm to cluster data. The proposed algorithm adopts a novel nonmetric distance measure based on the idea of “point symmetry.” This kind of “point symmetry distance” can be applied in data clustering and human face detection. Several data sets are used to illustrate its effectiveness.</p>
INDEX TERMS
Data clustering, pattern recognition, k-means algorithm, face detection.
CITATION
Mu-Chun Su, Chien-Hsing Chou, "A Modified Version of the K-Means Algorithm with a Distance Based on Cluster Symmetry", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 23, no. , pp. 674-680, June 2001, doi:10.1109/34.927466
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