Hybridization of the Ant Colony Optimization with the K-Means Algorithm for Clustering

  • Sara Saatchi
  • Chih Cheng Hung
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3540)

Abstract

In this paper the novel concept of ACO and its learning mechanism is integrated with the K-means algorithm to solve image clustering problems. The learning mechanism of the proposed algorithm is obtained by using the defined parameter called pheromone, by which undesired solutions of the K-means algorithm is omitted. The proposed method improves the K-means algorithm by making it less dependent on the initial parameters such as randomly chosen initial cluster centers, hence more stable.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Sara Saatchi
    • 1
  • Chih Cheng Hung
    • 1
  1. 1.Department of Computer ScienceSouthern Polytechnic State UniversityMariettaUSA

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