An unconditionally stable numerical method for bimodal image segmentation

Yibao Li, Junseok Kim

Research output: Contribution to journalArticle

17 Citations (Scopus)


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
Issue number6
Publication statusPublished - 2012 Nov 25



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

ASJC Scopus subject areas

  • Computational Mathematics
  • Applied Mathematics

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