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Bidirectional evolution of morphological level set for fast image segmentation

  • Guopu Zhu*
  • , Shuqun Zhang
  • *Corresponding author for this work
  • Sun Yat-Sen University
  • City University of New York

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

Abstract

We propose a novel level set method for fast image segmentation, which evolves level set functions using simple binary morphological operations. The proposed method is superior to a previously reported morphological level set method in capable of bidirectional evolution of level set functions, i.e., the interface of a level set function can either expand or shrink toward the object boundary. The experimental results on image segmentation show the high performance and fast computation of the proposed level set method, which also facilitates parallel hardware and optical implementation.

Original languageEnglish
Title of host publicationWMSCI 2011 - The 15th World Multi-Conference on Systemics, Cybernetics and Informatics, Proceedings
Pages281-284
Number of pages4
StatePublished - 2011
Externally publishedYes
Event15th World Multi-Conference on Systemics, Cybernetics and Informatics, WMSCI 2011 - Orlando, FL, United States
Duration: 19 Jul 201122 Jul 2011

Publication series

NameWMSCI 2011 - The 15th World Multi-Conference on Systemics, Cybernetics and Informatics, Proceedings
Volume1

Conference

Conference15th World Multi-Conference on Systemics, Cybernetics and Informatics, WMSCI 2011
Country/TerritoryUnited States
CityOrlando, FL
Period19/07/1122/07/11

Keywords

  • Image segmentation
  • Level set method
  • Morphological operation

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