An efficient line symmetry-based K-means algorithm

Authors:
Kuo-Liang Chung;Keng-Sheng Lin
Affiliations:
Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, No. 43, Section 4, Keelung Road, Taipei 10672, Taiwan;Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, No. 43, Section 4, Keelung Road, Taipei 10672, Taiwan
Venue:
Pattern Recognition Letters
Year:
2006

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Abstract

Recently, Su and Chou presented an efficient point symmetry-based K-means algorithm. Extending their point symmetry-based K-means algorithm, this paper presents a novel line symmetry-based K-means algorithm for clustering the data set with line symmetry property. Based on some real data sets, experimental results demonstrate that our proposed line symmetry-based K-means algorithm is rather encouraging.