Journal of Mathematical Imaging and Vision

, Volume 25, Issue 3, pp 365–386 | Cite as

Segmentation of Vectorial Image Features Using Shape Gradients and Information Measures

  • Ariane Herbulot
  • Stéphanie Jehan-Besson
  • Stefan Duffner
  • Michel Barlaud
  • Gilles Aubert
Article

Abstract

In this paper, we propose to focus on the segmentation of vectorial features (e.g. vector fields or color intensity) using region-based active contours. We search for a domain that minimizes a criterion based on homogeneity measures of the vectorial features. We choose to evaluate, within each region to be segmented, the average quantity of information carried out by the vectorial features, namely the joint entropy of vector components. We do not make any assumption on the underlying distribution of joint probability density functions of vector components, and so we evaluate the entropy using non parametric probability density functions. A local shape minimizer is then obtained through the evolution of a deformable domain in the direction of the shape gradient.

The first contribution of this paper lies in the methodological approach used to differentiate such a criterion. This approach is mainly based on shape optimization tools. The second one is the extension of this method to vectorial data. We apply this segmentation method on color images for the segmentation of color homogeneous regions. We then focus on the segmentation of synthetic vector fields and show interesting results where motion vector fields may be separated using both their length and their direction. Then, optical flow is estimated in real video sequences and segmented using the proposed technique. This leads to promising results for the segmentation of moving video objects.

Keywords

image segmentation active contours image statistics information information theory entropy joint probability shape optimization shape gradient motion segmentation 

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Copyright information

© Springer Science + Business Media, LLC 2006

Authors and Affiliations

  • Ariane Herbulot
    • 1
  • Stéphanie Jehan-Besson
    • 2
  • Stefan Duffner
    • 2
    • 4
  • Michel Barlaud
    • 1
  • Gilles Aubert
    • 3
  1. 1.Laboratoire I3S, CNRS-UNSASophia AntipolisFrance
  2. 2.Laboratoire GREYC-ImageCaenFrance
  3. 3.Laboratoire J.A. DieudonnéCNRS-UNSA,Parc ValroseNice Cedex 2France
  4. 4.Now with France Telecom R&DFrance

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