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Merging Active Contours

  • Ismail Ben Ayed
  • Amar Mitiche
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5359)

Abstract

In current active contour image segmentation methods, the number of regions is assumed to be known beforehand. It is related directly to a fixed number of active curves. How to allow it to vary is an important question which has been generally avoided. This study investigates a segmentation prior related to regions area to allow the number of regions to vary automatically during curve evolution, thereby optimizing the objective functional implicitly with respect to the number of regions. The obtained evolution equations show that the proposed prior can cause some curves to disappear while other curves expand, thereby leading to a region merging by curve evolution, although not in the sense of the traditional one-step merging of two regions. We give a statistical interpretation to the coefficient of this prior to balance its effect systematically against the other functional terms. We show the validity and efficiency of the method by testing on real images of intensity. A comparison demonstrates the advantages of the proposed method over the region-competition algorithm in regard to the optimal number of regions and computational load.

Keywords

Active Contour Initial Number Real Image Curve Evolution Data Term 
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 2008

Authors and Affiliations

  • Ismail Ben Ayed
    • 1
  • Amar Mitiche
    • 2
  1. 1.GE HealthcareLondonCanada
  2. 2.Institut National de la Recherche ScientifiqueINRS-EMTMontréalCanada

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