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Texture Description by Independent Components

  • Dick de Ridder
  • Robert P. W. Duin
  • Josef Kittler
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2396)

Abstract

A model for probabilistic independent component subspace analysis is developed and applied to texture description. Experiments show it to perform comparably to a Gaussian model, and to be useful mainly for problems in which the detection of little occurring, high-frequency image elements is important.

Keywords

Independent Component Analysis Independent Component Gaussian Model Texture Image Texture Description 
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 2002

Authors and Affiliations

  • Dick de Ridder
    • 1
  • Robert P. W. Duin
    • 1
  • Josef Kittler
    • 2
  1. 1.Pattern Recognition Group Dept. of Applied Physics, Faculty of Applied SciencesDelft University of TechnologyDelftThe Netherlands
  2. 2.Centre for Vision, Speech and Signal Processing School of Electronics, Computing and MathematicsUniversity of Surrey GuildfordSurreyUK

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