Combinatorial pyramids and discrete geometry for energy-minimizing segmentation

Abstract
This paper defines the basis of a new hierarchical framework for segmentation algorithms based on energy minimization schemes. This new framework is based on two formal tools. First, a combinatorial pyramid encode efficiently a hierarchy of partitions. Secondly, discrete geometric estimators measure precisely some important geometric parameters of the regions. These measures combined with photometrical and topological features of the partition allows to design energy terms based on discrete measures. Our segmentation framework exploits these energies to build a pyramid of image partitions with a minimization scheme. Some experiments illustrating our framework are shown and discussed.
Type
Publication
Proc. Int. Symposium on Visual Computing (ISVC'2006), Lake Tahoe, Nevada volume 4292 of Lecture Notes in Computer Science, pp 306-315, 2006. Springer
Combinatorial Pyramid
Multiscale Image Segmentation
Image Segmentation
Energy Minimization
Digital Geometry
2D
Image Analysis
Combinatorial Map
Variational Model

Authors
Professor of Computer Science
My research interests include digital geometry, geometry processing, image analysis, variational models and discrete calculus.