Computer Analysis of Images and Patterns

Volume 5702 of the series Lecture Notes in Computer Science pp 342-350

Graph-Based k-Means Clustering: A Comparison of the Set Median versus the Generalized Median Graph

  • M. FerrerAffiliated withLancaster UniversityInstitut de Robòtica i Informàtica Industrial, CSIC-UPC
  • , E. ValvenyAffiliated withLancaster UniversityCentre de Visió per Computador, Universitat Autònoma de Barcelona
  • , F. SerratosaAffiliated withCarnegie Mellon UniversityDepartament d’Informàtica i Matemàtiques, Universitat Rovira i Virgili
  • , I. BardajíAffiliated withLancaster UniversityInstitut de Robòtica i Informàtica Industrial, CSIC-UPC
  • , H. BunkeAffiliated withCarnegie Mellon UniversityInstitute of Computer Science and Applied Mathematics, University of Bern

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In this paper we propose the application of the generalized median graph in a graph-based k-means clustering algorithm. In the graph-based k-means algorithm, the centers of the clusters have been traditionally represented using the set median graph. We propose an approximate method for the generalized median graph computation that allows to use it to represent the centers of the clusters. Experiments on three databases show that using the generalized median graph as the clusters representative yields better results than the set median graph.