Texture based segmentation using graph cut and Gabor filters

  • Authors:
  • M. Jirik;T. Ryba;M. Zelezny

  • Affiliations:
  • The University of West Bohemia, Pilsen, Czech Republic;The University of West Bohemia, Pilsen, Czech Republic;The University of West Bohemia, Pilsen, Czech Republic

  • Venue:
  • Pattern Recognition and Image Analysis
  • Year:
  • 2011

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Abstract

This paper describes a method for texture based segmentation. Texture features are extracted by applying a bank of Gabor filters using two-sided convolution strategy. Probability texture model is represented by Gaussian mixture that is trained with the Expectation-maximization algorithm. Texture similarity, obtained this way, is used like the input of a Graph cut method. We show that the combination of texture analysis and the Graph cut method produce good results.