A Hybrid Data and Space Partitioning Technique for Similarity Queries on Bounded Clusters

  • Piyush K. Bhunre
  • C. A. Murthy
  • Arijit Bishnu
  • Bhargab B. Bhattacharya
  • Malay K. Kundu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3776)

Abstract

In this paper, a new method for generating size-bounded clusters is proposed such that the cardinality of each cluster is less than or equal to a pre-specified value. First, set estimation techniques coupled with Rectangular Intersection Graphs are used to generate adaptive clusters. Then, the size-bounded clusters are obtained by using space partitioning techniques. The clusters can be indexed by a Kd-tree like structure for similarity queries. The proposed method is likely to find applications to Content Based Image Retrieval (CBIR).

Keywords

Query Image Range Query Query Point Content Base Image Retrieval Cluster Centroid 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Piyush K. Bhunre
    • 1
  • C. A. Murthy
    • 2
  • Arijit Bishnu
    • 3
  • Bhargab B. Bhattacharya
    • 2
  • Malay K. Kundu
    • 2
  1. 1.National University of SingaporeSingapore
  2. 2.Indian Statistical InstituteKolkataIndia
  3. 3.Indian Institute of Technology, KharagpurKharagpurIndia

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