An efficient fractals-based algorithm for clustering

Fractals, sets that exhibit certain self-similarity, have attracted considerable attention in the past decade. They have been used to model a wide variety of natural phenomena. This paper presents a new algorithm based on fractals for clustering. In particular, an algorithm to cluster 2D data based...

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Published inIEEE TENCON 2003 : Conference on Convergent Technologies for the Asia-Pacific Region : October 15-17, 2003, Bangalore, India Vol. 1; pp. 244 - 246 Vol.1
Main Authors Prasad, M.G.P., Dube, S., Sridharan, K.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2003
Subjects
Clustering algorithms
Computational complexity
Data mining
Fractals
Image databases
Image segmentation
Java
Noise shaping
Partitioning algorithms
Shape
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ISBN0780381629
9780780381629
DOI10.1109/TENCON.2003.1273323

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Summary:Fractals, sets that exhibit certain self-similarity, have attracted considerable attention in the past decade. They have been used to model a wide variety of natural phenomena. This paper presents a new algorithm based on fractals for clustering. In particular, an algorithm to cluster 2D data based on the correlation dimension is presented. The algorithm is simple to implement and has low computational complexity. Experiments applying the algorithm to different datasets are presented and confirm the suitability of the approach for this application.
ISBN:0780381629
9780780381629
DOI:10.1109/TENCON.2003.1273323