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A Comparison of Spatial Pattern Spectra

  • Sander Land
  • Michael H. F. Wilkinson
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5720)

Abstract

Pattern spectra have frequently been used in image analysis. A drawback is that they are not sensitive to changes in spatial distribution of features. Various methods have been proposed to address this problem. In this paper we compare several of these on both texture classification and image retrieval. Results show that Size Density Spectra are most versatile, and least sensitive to parameter settings.

Keywords

Image Retrieval Query Image Query Expansion Mean Average Precision Pattern Spectrum 
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 2009

Authors and Affiliations

  • Sander Land
    • 1
  • Michael H. F. Wilkinson
    • 1
  1. 1.Institute for Mathematics and Computing ScienceUniversity of GroningenGroningenThe Netherlands

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