Iterated random walks with shape prior

  • Authors
  • Pujadas ER, Kjer HM, Piella G, González Ballester MA
  • UPF authors
  • PIELLA FENOY, GEMA; GONZALEZ BALLESTER, MIGUEL ANGEL; RUIZ PUJADAS, ESMERALDA;
  • Type
  • Scholarly articles
  • Journal títle
  • Image and Vision Computing
  • Publication year
  • 2016
  • Volume
  • 54
  • Number
  • 1
  • Pages
  • 12-21
  • ISSN
  • 0262-8856
  • Publication State
  • Published
  • Abstract
  • We propose a new framework for image segmentation using random walks where a distance shape prior is combined with a region term. The shape prior is weighted by a confidence map to reduce the influence of the prior in high gradient areas and the region term is computed with k-means to estimate the parametric probability density function. Then, random walks is performed iteratively aligning the prior with the current segmentation in every iteration. We tested the proposed approach with natural and medical images and compared it with the latest techniques with random walks and shape priors. The experiments suggest that this method gives promising results for medical and natural images
  • Complete citation
  • Pujadas ER, Kjer HM, Piella G, González Ballester MA. Iterated random walks with shape prior. Image and Vision Computing 2016; 54(1): 12-21.
Bibliometric indicators
  • 3 times cited Scopus
  • 2 times cited WOS
  • Índex Scimago de 0.954(2016)