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Self-similarity and Points of Interest in Textured Images

  • Shripad Kondra
  • Alfredo Petrosino
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7143)

Abstract

We propose the application of symmetry for texture classification. First we propose a feature vector based on the distribution of local bilateral symmetry in textured images. This feature is more effective in classifying a uniform texture versus a non-uniform texture. The feature when used with a texton-based feature improves the classification rate and is tested on 4 texture datasets. Secondly, we also present a global clustering of texture based on symmetry.

Keywords

Feature Vector Angle Distribution Symmetry Distribution Symmetry Operator Global Cluster 
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 2012

Authors and Affiliations

  • Shripad Kondra
    • 1
    • 2
  • Alfredo Petrosino
    • 2
  1. 1.Neuroimaging LabNational Brain Research CentreIndia
  2. 2.Department of Applied ScienceUniversity of Naples ”Parthenope”Italy

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