%0 Conference Proceedings
%T Image Segmentation by Image Foresting Transform with Non-smooth Connectivity Functions
%A Mansilla, Lucy Alsina Choque,
%A Miranda, Paulo André Vechiatto de,
%E Segundo, Maurício Pamplona,
%E Faria, Fabio Augusto,
%B Conference on Graphics, Patterns and Images, 28 (SIBGRAPI)
%8 Aug. 26-29, 2015
%I Sociedade Brasileira de Computação
%J Porto Alegre
%K cut, image foresting transform, oriented image foresting transform, non-smooth connectivity function, geodesic star convexity.
%X Image segmentation, such as to extract an object from a background, is very useful for medical and biological image analysis. In this work, we propose new methods for interactive segmentation of multidimensional images, based on the Image Foresting Transform (IFT), by exploiting for the first time non-smooth connectivity functions (NSCF) with a strong theoretical background. The new algorithms provide global optimum solutions according to an energy function of graph cut, subject to high-level boundary constraints (polarity and shape), or consist in a sequence of paths' optimization in residual graphs. Our experimental results indicate substantial improvements in accuracy in relation to other state-of-the-art methods, by allowing the customization of the segmentation to a given target object.