A Noise Tolerant Watershed Transformation with Viscous Force for Seeded Image Segmentation

  • Di Yang
  • Stephen Gould
  • Marcus Hutter
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7724)

Abstract

The watershed transform was proposed as a novel method for image segmentation over 30 years ago. Today it is still used as an elementary step in many powerful segmentation procedures. The watershed transform constitutes one of the main concepts of mathematical morphology as an important region-based image segmentation approach. However, the original watershed transform is highly sensitive to noise and is incapable of detecting objects with broken edges. Consequently its adoption in domains where imaging is subject to high noise is limited. By incorporating a high-order energy term into the original watershed transform, we proposed the viscous force watershed transform, which is more immune to noise and able to detect objects with broken edges.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Di Yang
    • 1
  • Stephen Gould
    • 1
  • Marcus Hutter
    • 1
  1. 1.Research School of Computer ScienceThe Australian National UniversityAustralia

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