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2010

Effective Level Set Image Segmentation With a Kernel Induced Data Term

8 years 7 months ago
Effective Level Set Image Segmentation With a Kernel Induced Data Term
Abstract—This study investigates level set multiphase image segmentation by kernel mapping and piecewise constant modeling of the image data thereof. A kernel function maps implicitly the original data into data of a higher dimension so that the piecewise constant model becomes applicable. This leads to a flexible and effective alternative to complex modeling of the image data. The method uses an active curve objective functional with two terms: an original term which evaluates the deviation of the mapped image data within each segmentation region from the piecewise constant model and a classic length regularization term for smooth region boundaries. Functional minimization is carried out by iterations of two consecutive steps: 1) minimization with respect to the segmentation by curve evolution via Euler-Lagrange descent equations and 2) minimization with respect to the regions parameters via fixed point iterations. Using a common kernel function, this step amounts to a mean shift ...
Mohamed Ben Salah, Amar Mitiche, Ismail Ben Ayed
Added 31 Jan 2011
Updated 31 Jan 2011
Type Journal
Year 2010
Where TIP
Authors Mohamed Ben Salah, Amar Mitiche, Ismail Ben Ayed
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