A Fast Level Set-Like Algorithm for Region-Based Active Contours

  • Martin Maška
  • Pavel Matula
  • Ondřej Daněk
  • Michal Kozubek
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6455)


Implicit active contours are widely employed in image processing and related areas. Their implementation using the level set framework brings several advantages over parametric snakes. In particular, a parameterization independence, topological flexibility, and straightforward extension into higher dimensions have led to their popularity. On the other hand, a numerical solution of associated partial differential equations (PDEs) is very time-consuming, especially for large 3D images. In this paper, we modify a fast level set-like algorithm by Nilsson and Heyden [14] intended for tracking gradient-based active contours in order to obtain a fast algorithm for tracking region-based active contours driven by the Chan-Vese model. The potential of the proposed algorithm and its comparison with two other fast methods minimizing the Chan-Vese model are demonstrated on both synthetic and real image data.


Active Contour Active Contour Model Initial Contour Speed Function Interface Point 
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 2010

Authors and Affiliations

  • Martin Maška
    • 1
  • Pavel Matula
    • 1
  • Ondřej Daněk
    • 1
  • Michal Kozubek
    • 1
  1. 1.Centre for Biomedical Image Analysis, Faculty of InformaticsMasaryk UniversityBrnoCzech Republic

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