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An Improved C-V Model without Reinitialization

We propose a novel improved C-V model without re-initialization to segment objects in an image. We introduce the deviation of level set function from the signed distance function into the C-V model (i.e., active contours without edges) to keep approximately the level set function as a signed distance function during the curve evolution. Therefore, in our model, the time-consuming re-initialization procedure is not necessary and it thus speeds up the curve evolution and the segmentation. Moreover, the level set function can be flexibly initialized with a piecewise constant function rather than a signed distance function in practice. Thereby the consuming time to compute a signed distance function from an initial curve in irregular shape is saved. The numerical algorithm of our model is implemented using the finite difference scheme.