A novel image clustering algorithm on peer-to-peer network

Kan Li*, Zheng Zhou

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

In order to decrease transmission data on P2P network and improve image clustering efficiency, an image clustering method is presented in the paper. We define the concepts of peer, class, group and overlay, which have their representation or signature, and describe the architecture of peer-to-peer network. In the method, the feature space is divided into units into which the feature vectors may be mapped, thus images can be represents by a simpler manner according to the partition units. We propose class similarity and group similarity algorithms, and give the peer clustering strategy. we use these methods to build the overlay network on which peers in one overlay are similar. Finally, the experiment results show that the proposed image clustering algorithm can reduce transmission content in the network while increase the performance.

Original languageEnglish
Pages (from-to)151-160
Number of pages10
JournalInternational Journal of Digital Content Technology and its Applications
Volume6
Issue number20
DOIs
Publication statusPublished - Nov 2012

Keywords

  • Image clustering
  • Multiway spectral clustering
  • Out-of-sample extensions
  • Peer-to-peer network

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