Iterated graph cuts for image segmentation

Bo Peng, Lei Zhang, Jian Yang

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

18 Citations (Scopus)

Abstract

Graph cuts based interactive segmentation has become very popular over the last decade. In standard graph cuts, the extraction of foreground object in a complex background often leads to many segmentation errors and the parameter λ in the energy function is hard to select. In this paper, we propose an iterated graph cuts algorithm, which starts from the sub-graph that comprises the user labeled foreground/ background regions and works iteratively to label the surrounding un-segmented regions. In each iteration, only the local neighboring regions to the labeled regions are involved in the optimization so that much interference from the far unknown regions can be significantly reduced. To improve the segmentation efficiency and robustness, we use the mean shift method to partition the image into homogenous regions, and then implement the proposed iterated graph cuts algorithm by taking each region, instead of each pixel, as the graph node for segmentation. Extensive experiments on benchmark datasets demonstrated that our method gives much better segmentation results than the standard graph cuts and the GrabCut methods in both qualitative and quantitative evaluation. Another important advantage is that it is insensitive to the parameter λ in optimization.
Original languageEnglish
Title of host publicationComputer Vision, ACCV 2009 - 9th Asian Conference on Computer Vision, Revised Selected Papers
Pages677-686
Number of pages10
EditionPART 2
DOIs
Publication statusPublished - 29 Dec 2010
Event9th Asian Conference on Computer Vision, ACCV 2009 - Xi'an, China
Duration: 23 Sep 200927 Sep 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume5995 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference9th Asian Conference on Computer Vision, ACCV 2009
Country/TerritoryChina
CityXi'an
Period23/09/0927/09/09

Keywords

  • Graph cuts
  • Image segmentation
  • Regions merging

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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