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

7 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
CountrySpain
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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