Robust Edge Detection Using Mumford-Shah Model and Binary Level Set Method

  • Li-Lian Wang
  • Yuying Shi
  • Xue-Cheng Tai
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6667)

Abstract

A new approximation of the Mumford-Shah model is proposed for edge detection, which could handle open-ended curves and closed curves as well. The essential idea is to treat the curves by narrow regions, and use a sharp interface technique to solve the approximate Mumford-Shah model. A fast algorithm based on the augmented Lagrangian method is developed. Numerical results show that the proposed model and method are very efficient and have the potential to be used for edge detections for real complicated images.

Keywords

Image Segmentation Edge Detection Active Contour Augmented Lagrangian Method Canny Edge Detector 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Li-Lian Wang
    • 1
  • Yuying Shi
    • 2
  • Xue-Cheng Tai
    • 1
    • 3
  1. 1.Division of Mathematical Sciences, School of Physical and Mathematical SciencesNanyang Technological UniversitySingapore
  2. 2.Department of Mathematics and PhysicsNorth China Electric Power UniversityBeijingChina
  3. 3.Department of MathematicsUniversity of BergenBergenNorway

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