A geometric-functional-based image segmentation and inpainting

Authors:
Vladimir Kluzner;Gershon Wolansky;Yehoshua Y. Zeevi
Affiliations:
Mathematics Department, Technion;Mathematics Department, Technion;Department of Electrical Engineering, Technion
Venue:
SSVM'07 Proceedings of the 1st international conference on Scale space and variational methods in computer vision
Year:
2007

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Abstract

The Mumford-Shah functional minimization, and related algorithms for image segmentation, involve a tradeoff between a two-dimensional image structure and one-dimensional parametric curves (contours) that surround objects or distinct regions in the image. We propose an alternative functional that is independent of parameterization; it is a geometric functional which is given in terms of the geometry of surfaces representing the data and image in a feature space. The Γ-convergence technique is combined with the minimal surface theory in order to yield a global generalization of the Mumford-Shah segmentation functional.