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A novel variational model for image segmentation

  • Harbin Institute of Technology

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper, we propose a new variational model for image segmentation. Our model is inspired by the complex GinzburgLandau model and the semi-norm defined by us. This new model can detect both the convex and concave parts of images. Moreover, it can also detect non-closed edges as well as quadruple junctions. Compared with other methods, the initialization is completely automatic and the segmented images obtained by using our new model could keep fine structures and edges of the original images very effectively. Finally, numerical results show the effectiveness of our model.

Original languageEnglish
Pages (from-to)2234-2241
Number of pages8
JournalJournal of Computational and Applied Mathematics
Volume235
Issue number8
DOIs
StatePublished - 15 Feb 2011

Keywords

  • GinzburgLandau model
  • Image segmentation
  • Semi-norm

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