Comparison of Two Fast Nearest-Neighbour Search Methods in High-Dimensional Large-Sized Databases

  • Javier Cano
  • Juan-Carlos Pérez-Cortés
  • Ismael Salvador
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3138)


In this paper we show the results of a performance comparison between two Nearest Neighbour Search Methods: one, proposed by Arya & Mount, is based on a kd–tree data structure and a Branch and Bound approximate search algorithm [1], and the other is a search method based on dimensionality projections, presented by Nene & Nayar in [5]. A number of experiments have been carried out in order to find the best choice to work with high dimensional points and large data sets.


Test Point Query Point Candidate List Rank Number Tree Data Structure 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Javier Cano
    • 1
  • Juan-Carlos Pérez-Cortés
    • 1
  • Ismael Salvador
    • 1
  1. 1.Instituto Tecnológico de InformáticaUniversidad Politécnica de ValenciaValenciaSpain

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