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Application of the Level-Set Model with Constraints in Image Segmentation

  • Vladimír Klement (a1), Tomáš Oberhuber (a1) and Daniel Ševčovič (a2)
Abstract
Abstract

We propose and analyze a constrained level-set method for semi-automatic image segmentation. Our level-set model with constraints on the level-set function enables us to specify which parts of the image lie inside respectively outside the segmented objects. Such a-priori information can be expressed in terms of upper and lower constraints prescribed for the level-set function. Constraints have the same conceptual meaning as initial seeds of the popular graph-cuts based methods for image segmentation. A numerical approximation scheme is based on the complementary-finite volumes method combined with the Projected successive over-relaxation method adopted for solving constrained linear complementarity problems. The advantage of the constrained level-set method is demonstrated on several artificial images as well as on cardiac MRI data.

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*Corresponding author. Email addresses: tomas.oberhuber@fjfi.cvut.cz (T. Oberhuber), vladimir.klement@fjfi.cvut.cz (V. Klement), sevcovic@fmph.uniba.sk (D. Ševčovič)
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Numerical Mathematics: Theory, Methods and Applications
  • ISSN: 1004-8979
  • EISSN: 2079-7338
  • URL: /core/journals/numerical-mathematics-theory-methods-and-applications
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