An unconditionally stable numerical method for bimodal image segmentation

Yibao Li, Junseok Kim

Research output: Contribution to journalArticle

17 Citations (Scopus)

Abstract

In this paper, we propose a new level set-based model and an unconditionally stable numerical method for bimodal image segmentation. Our model is based on the Lee-Seo active contour model. The numerical scheme is semi-implicit and solved by an analytical method. The unconditional stability of the proposed numerical method is proved analytically. We demonstrate performance of the proposed image segmentation algorithm on several synthetic and real images to confirm the efficiency and stability of the proposed method.

Original languageEnglish
Pages (from-to)3083-3090
Number of pages8
JournalApplied Mathematics and Computation
Volume219
Issue number6
DOIs
Publication statusPublished - 2012 Nov 25

Fingerprint

Unconditionally Stable
Bimodal
Image segmentation
Image Segmentation
Numerical methods
Numerical Methods
Unconditional Stability
Active Contour Model
Semi-implicit
Analytical Methods
Level Set
Numerical Scheme
Convergence of numerical methods
Model
Demonstrate

Keywords

  • Chan-Vese model
  • Energy minimization
  • Image segmentation
  • Lee-Seo model
  • Level set model
  • Unconditional stability

ASJC Scopus subject areas

  • Applied Mathematics
  • Computational Mathematics

Cite this

An unconditionally stable numerical method for bimodal image segmentation. / Li, Yibao; Kim, Junseok.

In: Applied Mathematics and Computation, Vol. 219, No. 6, 25.11.2012, p. 3083-3090.

Research output: Contribution to journalArticle

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