Image segmentation based on geodesic aided Chan-Vese model

Thi Thao Tran, Van Truong Pham, Yun Jen Chiu, Kuo Kai Shyu

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

7 Scopus citations

Abstract

In this paper, a novel model for intensity inhomogeneous image segmentation is proposed. The proposed model uses the local information of the image to be segmented; concurrently, it incorporates the geodesic active contour (GAC) model into Chan-Vese (C-V) model in energy function. Thus, the proposed model is effective when dealing with intensity inhomogeneous images. Practical experiments prove that the proposed model can obtain exact segmented results, especially with the intensity inhomogeneous images even with hole, noise and complex background.

Original languageEnglish
Title of host publicationProceedings - 2010 3rd IEEE International Conference on Computer Science and Information Technology, ICCSIT 2010
Pages315-317
Number of pages3
DOIs
StatePublished - 2010
Event2010 3rd IEEE International Conference on Computer Science and Information Technology, ICCSIT 2010 - Chengdu, China
Duration: 9 Jul 201011 Jul 2010

Publication series

NameProceedings - 2010 3rd IEEE International Conference on Computer Science and Information Technology, ICCSIT 2010
Volume1

Conference

Conference2010 3rd IEEE International Conference on Computer Science and Information Technology, ICCSIT 2010
Country/TerritoryChina
CityChengdu
Period9/07/1011/07/10

Keywords

  • Active contour
  • Chan-Vese model
  • Geodesic active contour model
  • Image segmentation
  • Level set method

Fingerprint

Dive into the research topics of 'Image segmentation based on geodesic aided Chan-Vese model'. Together they form a unique fingerprint.

Cite this