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From Inpainting to Active Contours

  • François Lauze
  • Mads Nielsen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3752)

Abstract

We introduce a novel type of region based active contour using image inpainting. Usual region based active contours assume that the image is divided into several semantically meaningful regions and attempt to differentiate them through recovering dynamically statistical optimal parameters for each region. In case when perceptually distinct regions have similar intensity distributions, the methods mentioned above fail. In this work, we formulate the problem as optimizing a ”background disocclusion” criterion, a disocclusion that can be performed by inpainting. We look especially at a family of inpainting formulations that includes the Chan and Shen Total Variation Inpainting (more precisely a regularization of it). In this case, the optimization leads formally to a coupled contour evolution equation, an inpainting equation, as well as a linear PDE depending on the inpainting. The contour evolution is implemented in the framework of level sets. Finally, the proposed method is validated on various examples.

Keywords

Computer Vision Active Contour Active Contour Model Image Inpainting Shape Derivative 
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 2005

Authors and Affiliations

  • François Lauze
    • 1
  • Mads Nielsen
    • 1
  1. 1.Departement of InnovationThe IT University of CopenhagenDenmark

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