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Texture Granularities

  • Paul Southam
  • Richard Harvey
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3617)

Abstract

We introduce three new texture features that are based on the morphological scale-space operator known as the sieve. The new features are tested on two databases. The first, the Outex texture database, contains Brodatz-like textures captured under constant illumination, scale and rotation. The second, the Outex natural scene database, contains images of real-world scenes taken under variable conditions. The new features are compared to univariate granulometries, with which they have some similarities, and to the dual-tree complex wavelet transform, local binary patterns and co-occurrence matrices. The features based upon the sieve are shown to have the best overall performance.

Keywords

Texture Feature Local Binary Pattern Texture Granularity Digital Mammogram Granule Image 
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

  • Paul Southam
    • 1
  • Richard Harvey
    • 1
  1. 1.University of East AngliaNorwich, NorfolkEngland

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