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Adaptive diffusion flow for parametric active contours

  • Yuwei Wu*
  • , Yunde Jia
  • , Yuanquan Wang
  • *Corresponding author for this work
  • Beijing Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper proposes a novel external force for active contours, called adaptive diffusion flow (ADF). We reconsider the generative mechanism of gradient vector flow (GVF) diffusion process from the perspective of image restoration, and exploit a harmonic hypersurface minimal function to substitute smoothness energy term of GVF for alleviating the possible leakage problem. Meanwhile, a ∞ functional is incorporated in the ADF framework to ensure that the vector flow diffuses mainly along normal direction in homogenous regions of an image. Experiments on synthetic and real images demonstrate the good properties of the ADF snake, including noise robustness, weak edge preserving, and concavity convergence.

Original languageEnglish
Title of host publicationProceedings - 2010 20th International Conference on Pattern Recognition, ICPR 2010
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2788-2791
Number of pages4
ISBN (Print)9780769541099
DOIs
Publication statusPublished - 2010
Externally publishedYes

Publication series

NameProceedings - International Conference on Pattern Recognition
ISSN (Print)1051-4651

Keywords

  • Active contours
  • Adaptive diffusion flow
  • Gradient vector flow
  • Image segmentation

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