Image Segmentation by Image Foresting Transform with Non-smooth Connectivity Functions
Lucy A. Choque Mansilla$^{1}$
$^{1}$University of Sao Paulo. São Paulo-SP Brazil
Schedule:Thu 22st@15:45, Room: A

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.


	author 		= {Lucy A. Choque Mansilla},
	title 		= {Image Segmentation by Image Foresting Transform with Non-smooth Connectivity Functions},
	booktitle 	= {2015 XLI Latin American Computing Conference (CLEI), Special Edition},
	pages 		= {99--117},
	year 		= {2015},
	editor 		= {Universidad Católica San Pablo},
	address 	= {Arequipa-Peru},
	month 		= {October},
	organization 	= {CLEI},
	publisher 	= {CLEI},
	url 		= {},
	isbn 		= {978-9972-825-91-0},

Generated by Ernesto Cuadros-Vargas , Sociedad Peruana de Computación-Peru, Universidad Católica San Pablo, Arequipa-Perú