Discrete deformable boundaries for the segmentation of multidimensional images

Abstract

Energy-minimizing techniques are an interesting approach to the segmentation problem. They extract image components by deforming a geometric model according to energy constraints. This paper pro­poses an extension to these works, which can segment arbitrarily complex image components in any dimension. The geometric model is a digital surface with which an energy is associated. The model grows inside the component to segment by following minimal energy paths. The segmentation result is obtained em a posteriori by examining the energies of the successive model shapes. We validate our approach on several 2D images.

Jacques-Olivier Lachaud

Professor of Computer Science

My research interests include digital geometry, geometry processing, image analysis, variational models and discrete calculus.