Active contours based on Chambolle's mean curvature motion

Xavier Bresson*, Tony F. Chan

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

17 Scopus citations

Abstract

This paper proposes an algorithm to solve most of existing active contour problems based on the approach of mean curvature motion proposed by Chambolle in [1] and the image denoising model of Rudin, Osher and Fatemi (ROF) introduced in [2]. More precisely, the motion of active contours is discritized by the ROF model applied to the signed distance of the evolving contour. The advantage of this new discretization scheme is to use a time step much larger than in standard explicit schemes, which means that less iterations are needed to converge to the steady state solution. We present results on 2-D natural images.

Original languageEnglish (US)
Title of host publication2007 IEEE International Conference on Image Processing, ICIP 2007 Proceedings
Volume1
DOIs
StatePublished - Dec 1 2006
Externally publishedYes
Event14th IEEE International Conference on Image Processing, ICIP 2007 - San Antonio, TX, United States
Duration: Sep 16 2007Sep 19 2007

Publication series

NameProceedings - International Conference on Image Processing, ICIP
Volume1
ISSN (Print)1522-4880

Conference

Conference14th IEEE International Conference on Image Processing, ICIP 2007
CountryUnited States
CitySan Antonio, TX
Period09/16/0709/19/07

Keywords

  • Active contour
  • Image segmentation
  • Object extraction
  • ROF model
  • Signed distance function

ASJC Scopus subject areas

  • Engineering(all)

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