A graph-based clustering method and its applications

Authors:
Pasquale Foggia;Gennaro Percannella;Carlo Sansone;Mario Vento
Affiliations:
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II, Napoli, Italy;Dipartimento di Ingegneria dell'Informazione ed Ingegneria Elettrica, Università di Salerno, Fisciano, SA, Italy;Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II, Napoli, Italy;Dipartimento di Ingegneria dell'Informazione ed Ingegneria Elettrica, Università di Salerno, Fisciano, SA, Italy
Venue:
BVAI'07 Proceedings of the 2nd international conference on Advances in brain, vision and artificial intelligence
Year:
2007

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Abstract

In this paper we present a graph-based clustering method particularly suited for dealing with data that do not come from a Gaussian or a spherical distribution. It can be used for detecting clusters of any size and shape, without the need of specifying neither the actual number of clusters nor other parameters. The method has been tested on data coming from two different computer vision applications. A comparison with other three state-of-the-art algorithms was also provided, demonstrating the effectiveness of the proposed approach.