Image Segmentation Using Active Contours and Evidential Distance

  • Foued Derraz
  • Antonio Pinti
  • Miloud Boussahla
  • Laurent Peyrodie
  • Hechmi Toumi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8258)


We proposed a new segmentation based on Active Contours (AC) for vector-valued image that incorporates evidential distance. The proposed method combine both Belief Functions (BFs) and probability functions in the Bhattacharyya distance framework. This formulation allows all features issued from vector-valued image and guide the evolution of AC using an inside/outside descriptor. The imprecision caused by the variation of the contrast issued from the multiple channels is incorporated in the BFs as weighted parameters. We demonstrated the performance of the proposed algorithm using some challenging color biomedical images.


Active Contours Characteristic function Belief Function Bhattacharyya distance Dempster Shafer rule 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Foued Derraz
    • 1
    • 3
  • Antonio Pinti
    • 4
    • 5
  • Miloud Boussahla
    • 3
  • Laurent Peyrodie
    • 2
  • Hechmi Toumi
    • 5
  1. 1.Facult Libre de MdicineInstitut Catholique de Lille, Universit Catholique de LilleFrance
  2. 2.Hautes Etudes d’IngenieurUniversit Catholique de LilleFrance
  3. 3.Telecommunication Laboratory, Technology FacultyAbou Bekr Belkaid UniversityTlemcenAlgeria
  4. 4.ENSIAME UVHCUniversite de ValenciennesFrance
  5. 5.A5 EA 4708, I3MTO, CHROOrlansFrance

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