Abstract
In this paper, we propose a new 2D segmentation model including geometric constraints, namely interpolation conditions, to detect objects in a given image. We propose to apply the deformable models to an explicit function using the level set approach (Osher and Sethian [24]); so, we avoid the classical problem of parameterization of both segmentation representation and interpolation conditions. Furthermore, we allow this representation to have topological changes. A problem of energy minimization on a closed subspace of a Hilbert space is defined and introducing Lagrange multipliers enables us to formulate the corresponding variational problem with interpolation conditions. Thus the explicit function evolves, while minimizing the energy and it stops evolving when the desired outlines of the object to detect are reached. The stopping term, as in the classical deformable models, is related to the gradient of the image. Numerical results are given.
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Le Guyader, C., Apprato, D. & Gout, C. Using a level set approach for image segmentation under interpolation conditions. Numer Algor 39, 221–235 (2005). https://doi.org/10.1007/s11075-004-3631-z
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DOI: https://doi.org/10.1007/s11075-004-3631-z