• français
    • English
  • English 
    • français
    • English
  • Login
JavaScript is disabled for your browser. Some features of this site may not work without it.
BIRD Home

Browse

This CollectionBy Issue DateAuthorsTitlesSubjectsJournals BIRDResearch centres & CollectionsBy Issue DateAuthorsTitlesSubjectsJournals

My Account

Login

Statistics

View Usage Statistics

Fast Asymmetric Fronts Propagation for Image Segmentation

Thumbnail
View/Open
1809.07987.pdf (5.476Mb)
Date
2018
Link to item file
https://hal.archives-ouvertes.fr/hal-01963468
Dewey
Traitement du signal
Sujet
Finsler Metric; Randers Metric; Eikonal partial differential equation; Fast marching method; Image segmentation; Tubular structure segmentation
Journal issue
Journal of Mathematical Imaging and Vision
Volume
60
Number
6
Publication date
07-2018
Article pages
766-783
Publisher
Springer
DOI
http://dx.doi.org/10.1007/s10851-017-0776-7
URI
https://basepub.dauphine.fr/handle/123456789/18658
Collections
  • CEREMADE : Publications
Metadata
Show full item record
Author
Chen, Da
60 CEntre de REcherches en MAthématiques de la DEcision [CEREMADE]
Cohen, Laurent D.
60 CEntre de REcherches en MAthématiques de la DEcision [CEREMADE]
Type
Article accepté pour publication ou publié
Abstract (EN)
In this paper, we introduce a generalized asymmetric fronts propagation model based on the geodesic distance maps and the Eikonal partial differential equations. One of the key ingredients for the computation of the geodesic distance map is the geodesic metric, which can govern the action of the geodesic distance level set propagation. We consider a Finsler metric with the Randers form, through which the asymmetry and anisotropy enhancements can be taken into account to prevent the fronts leaking problem during the fronts propagation. These enhancements can be derived from the image edge-dependent vector field such as the gradient vector flow. The numerical implementations are carried out by the Finsler variant of the fast marching method, leading to very efficient interactive segmentation schemes. We apply the proposed Finsler fronts propagation model to image segmentation applications. Specifically, the foreground and background segmentation is implemented by the Voronoi index map. In addition, for the application of tubularity segmentation, we exploit the level set lines of the geodesic distance map associated with the proposed Finsler metric providing that a thresholding value is given.

  • Accueil Bibliothèque
  • Site de l'Université Paris-Dauphine
  • Contact
SCD Paris Dauphine - Place du Maréchal de Lattre de Tassigny 75775 Paris Cedex 16

 Content on this site is licensed under a Creative Commons 2.0 France (CC BY-NC-ND 2.0) license.