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Object segmentation based on watershed and graph cut

  • Yanmin Peng*
  • , Rong Liu
  • *Corresponding author for this work
  • Beihang University

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

Abstract

In this paper we select the inner contour and outer contour of the target object, and then apply watershed algorithm to divide the region between the inner contour and the outer contour into series of smaller regions. Each smaller region is regarded as a node, and the small regions contains of the inner contour are regarded as the source s, and the small regions contains of the outer contour are regarded as the sink t. Then from the source to the sink establishes a graph. Merging the capacities of parallel edges, deleting unnecessarily edges, multi-source and multi-sink can be converted to the single source and the single sink. And then minimum energy can be obtained by the maximal-flow cut, and the target object can be extracted. The experiment proves that this algorithm is effective in the segmentation than the other traditional algorithms, and has better performance in the running time.

Original languageEnglish
Title of host publicationProceedings - 2010 3rd International Congress on Image and Signal Processing, CISP 2010
Pages1431-1435
Number of pages5
DOIs
StatePublished - 2010
Event2010 3rd International Congress on Image and Signal Processing, CISP 2010 - Yantai, China
Duration: 16 Oct 201018 Oct 2010

Publication series

NameProceedings - 2010 3rd International Congress on Image and Signal Processing, CISP 2010
Volume3

Conference

Conference2010 3rd International Congress on Image and Signal Processing, CISP 2010
Country/TerritoryChina
CityYantai
Period16/10/1018/10/10

Keywords

  • Graph cut
  • Image processing
  • Max flow/min cut
  • Watershed algorithm

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