Multi-scale Binary Patterns for Texture Analysis

  • Topi Mäenpää
  • Matti Pietikäinen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2749)

Abstract

This paper presents two novel ways of extending the local binary pattern (LBP) texture analysis operator to multiple scales. First, large-scale texture patterns are detected by combining exponentially growing circular neighborhoods with Gaussian low-pass filtering. Second, cellular automata are proposed as a way of compactly encoding arbitrarily large circular neighborhoods. The performance of the extensions is evaluated in classifying natural textures from the Outex database.

Keywords

Cellular Automaton Local Binary Pattern Image Texture Large Neighborhood Neighborhood Radius 
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.

References

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Topi Mäenpää
    • 1
  • Matti Pietikäinen
    • 1
  1. 1.Machine Vision GroupInfotech Oulu University of OuluFinland

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