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Abstract

When patterns are represented as histograms, the earth mover’s distance, EMD has been considered an excellent metric between two distributions. EMD is formulated as the transportation problem which is a hard optimization problem. In similarity based pattern retrieval problems, computing EMDs for all histograms in the database against a query histogram would take too long time for users to wait for the output. Hence, the candidate selection technique is presented to speed up the EMD based multivariate ordinal type histogram retrieval problem. It guarantees to find all similar histograms while achieving significant speed up. Theoretical relationships between other metrics for multivariate histograms and their usages are presented as well.

Keywords

Transportation Problem Edit Distance Cost Matrix Retrieval Problem City Block Distance 
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 2008

Authors and Affiliations

  • Sung-Hyuk Cha
    • 1
  1. 1.Department of Computer SciencePace UniversityPleasantville

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