Local 2D Pattern Spectra as Connected Region Descriptors

  • Petra Bosilj
  • Michael H. F. Wilkinson
  • Ewa Kijak
  • Sébastien Lefèvre
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9082)

Abstract

We validate the usage of augmented 2D shape-size pattern spectra, calculated on arbitrary connected regions. The evaluation is performed on MSER regions and competitive performance with SIFT descriptors achieved in a simple retrieval system, by combining the local pattern spectra with normalized central moments. An additional advantage of the proposed descriptors is their size: being half the size of SIFT, they can handle larger databases in a time-efficient manner. We focus in this paper on presenting the challenges faced when transitioning from global pattern spectra to the local ones. An exhaustive study on the parameters and the properties of the newly constructed descriptor is the main contribution offered. We also consider possible improvements to the quality and computation efficiency of the proposed local descriptors.

Keywords

Shape-size pattern spectra Granulometries Max-tree Region descriptors CBIR 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Petra Bosilj
    • 1
  • Michael H. F. Wilkinson
    • 2
  • Ewa Kijak
    • 3
  • Sébastien Lefèvre
    • 1
  1. 1.Université de Bretagne-Sud - IRISAVannesFrance
  2. 2.Johann Bernoulli InstituteUniversity of GroningenGroningenThe Netherlands
  3. 3.Université de Rennes 1 - IRISARennesFrance

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