Fast Unsupervised Texture Segmentation Using Active Contours Model Driven by Bhattacharyya Gradient Flow

  • Foued Derraz
  • Abdelmalik Taleb-Ahmed
  • Antonio Pinti
  • Laurent Peyrodie
  • Nacim Betrouni
  • Azzeddine Chikh
  • Fethi Bereksi-Reguig
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5856)


We present a new unsupervised segmentation based active contours model and texture descriptor. The proposed texture descriptor intrinsically describes the geometry of textural regions using the shape operator defined in Beltrami framework. We use Bhattacharyya distance to discriminate textures by maximizing distance between the probability density functions which leads to distinguish textural objects of interest and background. We propose a fast Bregman split implementation of our segmentation algorithm based on the dual formulation of the Total Variation norm. Finally, we show results on some challenging images to illustrate segmentations that are possible.


Active contours texture descriptor bhattacharyya distance total variation Bregman split algorithm 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Foued Derraz
    • 1
    • 2
  • Abdelmalik Taleb-Ahmed
    • 1
  • Antonio Pinti
    • 1
  • Laurent Peyrodie
    • 4
  • Nacim Betrouni
    • 3
  • Azzeddine Chikh
    • 2
  • Fethi Bereksi-Reguig
    • 2
  1. 1.LAMIH UMR CNRS 8530ValenciennesFrance
  2. 2.GBM LaboratoryAbou Bekr Belkaid universityTlemcenAlgeria
  3. 3.LAMIH UMR CNRS 8530Valenciennes
  4. 4.Hautes Etudes d’Ingénieur LilleFrance

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