Context-Based Energy Estimator: Application to Object Segmentation on the Tree of Shapes

Authors

Yongchao Xu, Thierry Géraud, Laurent Najman

Where

Proceedings of the 19th International Conference on Image Processing (ICIP)

Place

Orlando, Florida, USA

Type

inproceedings

Publisher

IEEE

Keywords

Image

Date

2012-04-17

Abstract

Image segmentation can be defined as the detection of closed contours surrounding objects of interest. Given a family of closed curves obtained by some means, a difficulty is to extract the relevant ones. A classical approach is to define an energy minimization frameworkwhere interesting contours correspond to local minima of this energy. Active contours, graph cuts or minimum ratio cuts are instances of such approaches. In this article, we propose a novel, efficient ratio-cut estimator, which is both context-based and can be interpreted as an active contour. As a first example of the effectiveness of our formulation, we consider the tree of shapes, which provides a family of level lines organized in a tree hierarchy through an inclusion relationship. Thanks to the tree structure, the estimator can be computed incrementally in an efficient fashion. Experimental results on synthetic and real images demonstrate the robustness and usefulness of our method.

Documents

• Paper

Bibtex (lrde.bib)

@InProceedings{	  xu.12.icip,
  author	= {Yongchao Xu and Thierry G\'eraud and Laurent Najman},
  title		= {Context-Based Energy Estimator: Application to Object
		  Segmentation on the Tree of Shapes},
  booktitle	= {Proceedings of the 19th International Conference on Image
		  Processing (ICIP)},
  year		= 2012,
  address	= {Orlando, Florida, USA},
  month		= oct,
  organization	= {IEEE},
  publisher	= {IEEE},
  project	= {Image},
  abstract	= {Image segmentation can be defined as the detection of
		  closed contours surrounding objects of interest. Given a
		  family of closed curves obtained by some means, a
		  difficulty is to extract the relevant ones. A classical
		  approach is to define an energy minimization framework,
		  where interesting contours correspond to local minima of
		  this energy. Active contours, graph cuts or minimum ratio
		  cuts are instances of such approaches. In this article, we
		  propose a novel, efficient ratio-cut estimator, which is
		  both context-based and can be interpreted as an active
		  contour. As a first example of the effectiveness of our
		  formulation, we consider the tree of shapes, which provides
		  a family of level lines organized in a tree hierarchy
		  through an inclusion relationship. Thanks to the tree
		  structure, the estimator can be computed incrementally in
		  an efficient fashion. Experimental results on synthetic and
		  real images demonstrate the robustness and usefulness of
		  our method.}
}