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Geometric Structure and Randomness in Texture Analysis and Synthesis

  • Georgy Gimel’farb
  • Linjiang Yu
  • Dongxiao Zhou
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2616)

Abstract

Gibbs random field models describe image textures in terms of geometric structure and energy of pixel interactions. The interaction means statistical interdependence of signals, the structure is given by characteristic pixel neighbourhoods, and the energy depends on signal co- occurrences over the neighbourhoods. In translation invariant textures all the neighbourhoods have the same relative geometry. The interaction structure of such a texture is reflected in a model-based interaction map (MBIM) giving spatial distribution of the interaction energies over a large neighbourhood. We show that due to scale / orientation robustness, the MBIM allows to partition a given training sample into tiles acting as structural elements, or texels. Large-size textured images can be synthesised by replicating the training texels.

Keywords

Training Sample Texture Analysis Geometric Structure Pixel Neighbourhood Texture Synthesis 
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 2003

Authors and Affiliations

  • Georgy Gimel’farb
    • 1
  • Linjiang Yu
    • 1
  • Dongxiao Zhou
    • 1
  1. 1.Centre for Image Technology and Robotics Department of Computer Science, Tamaki CampusUniversity of AucklandAucklandNew Zealand

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