Texture Classification and Segmentation

  • Matti Pietikäinen
  • Abdenour Hadid
  • Guoying Zhao
  • Timo Ahonen
Part of the Computational Imaging and Vision book series (CIVI, volume 40)


The first part of this chapter provides an introduction to the most common texture image test sets and overviews some texture classification experiments involving LBP descriptors. An unsupervised method for texture segmentation using LBP and contrast (LBP/C) distributions is presented in the second part of the chapter. This method has become very popular, and many variants of it have been proposed, for example for color-texture segmentation and segmentation of remotely sensed images.


Texture Image Texture Classification Natural Scene Texture Segmentation Texture Boundary 
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 London Limited 2011

Authors and Affiliations

  • Matti Pietikäinen
    • 1
  • Abdenour Hadid
    • 1
  • Guoying Zhao
    • 1
  • Timo Ahonen
    • 2
  1. 1.Machine Vision Group, Department of Computer Science and EngineeringUniversity of OuluOuluFinland
  2. 2.Nokia Research CenterPalo AltoUSA

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