Primal-dual method for continuous max-flow approaches

Ke Wei, Xue Cheng Tai, Tony Chan, Shingyu Leung

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

8 Scopus citations

Abstract

We review the continuous max-flow approaches for the variational image segmentation models with piecewise constant representations. The review is conducted by exploring the primal-dual relationships between the continuous min-cut and max-flow problems. In addition, we introduce the parameter free primal-dual method for solving those max-flow problems. Empirical results show that the primal-dual method is competitive to the augmented Lagrangian method.

Original languageEnglish (US)
Title of host publicationComputational Vision and Medical Image Processing V - Proceedings of 5th Eccomas Thematic Conference on Computational Vision and Medical Image Processing, VipIMAGE 2015
EditorsJoao Manuel R.S. Tavares, R.M. Natal Jorge
PublisherCRC Press/Balkema
Pages17-24
Number of pages8
ISBN (Print)9781138029262
StatePublished - Jan 1 2016
Event5th Eccomas Thematic Conference on Computational Vision and Medical Image Processing, VipIMAGE 2015 - Tenerife, Spain
Duration: Oct 19 2015Oct 21 2015

Publication series

NameComputational Vision and Medical Image Processing V - Proceedings of 5th Eccomas Thematic Conference on Computational Vision and Medical Image Processing, VipIMAGE 2015

Conference

Conference5th Eccomas Thematic Conference on Computational Vision and Medical Image Processing, VipIMAGE 2015
Country/TerritorySpain
CityTenerife
Period10/19/1510/21/15

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Biomedical Engineering
  • Electrical and Electronic Engineering

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