Variational image binarization and its multi-scale realizations

Chong Sze TONG*, Yongping Zhang, Nanning Zheng

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

12 Citations (Scopus)


A variational approach for image binarization is discussed in this paper. The approach is based on the interpolation of surface. This interpolation is computed using edge points as interpolating points and minimizing an energy functional which interpolates a smooth threshold surface. A globally convergent Sequential Relaxation Algorithm (SRA) is proposed for solving the optimization problem. Moreover, our algorithm is also formulated in a multi-scale framework. The performance of our method is demonstrated on a variety of real and synthetic images and compared with traditional techniques. Examples show that our method gives promising results.

Original languageEnglish
Pages (from-to)185-198
Number of pages14
JournalJournal of Mathematical Imaging and Vision
Issue number2
Publication statusPublished - Sept 2005

Scopus Subject Areas

  • Statistics and Probability
  • Modelling and Simulation
  • Condensed Matter Physics
  • Computer Vision and Pattern Recognition
  • Geometry and Topology
  • Applied Mathematics

User-Defined Keywords

  • Global convergence
  • Image segmentation
  • Multi-scale image processing
  • Sequential relaxation algorithm
  • Variational approach


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