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Segmentation Using SubMarkov Random Walk

  • Xingping Dong
  • Jianbing Shen
  • Luc Van Gool
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8932)

Abstract

In this paper, we propose a subMarkov random walk (subRW) with the label prior with added auxiliary nodes for seeded image segmentation. We unify the proposed subRW and the other popular random walk algorithms. This unifying view can transfer the intrinsic findings between different random walk algorithms, and offer the new ideas for designing the novel random walk algorithms by changing the auxiliary nodes. According to the second benefit, we design a subRW algorithm with label prior to solve the segmentation problem of objects with thin and elongated parts. The experimental results on natural images with twigs demonstrate that our algorithm achieves better performance than the previous random walk algorithms.

Keywords

Segmentation subMarkov random walk auxiliary nodes 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Xingping Dong
    • 1
  • Jianbing Shen
    • 1
  • Luc Van Gool
    • 2
  1. 1.Beijing Laboratory of Intelligent Information Technology, School of Computer ScienceBeijing Institute of TechnologyBeijingP.R. China
  2. 2.Computer Vision LaboratoryETH ZurichZurichSwitzerland

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