• DocumentCode
    870068
  • Title

    Gradient vector flow fast geometric active contours

  • Author

    Paragios, Nikos ; Mellina-Gottardo, Olivier ; Ramesh, Visvanathan

  • Author_Institution
    Real-Time Vision & Modeling Dept., Siemens Corp. Res., Princeton, NJ, USA
  • Volume
    26
  • Issue
    3
  • fYear
    2004
  • fDate
    3/1/2004 12:00:00 AM
  • Firstpage
    402
  • Lastpage
    407
  • Abstract
    In this paper, we propose an edge-driven bidirectional geometric flow for boundary extraction. To this end, we combine the geodesic active contour flow and the gradient vector flow external force for snakes. The resulting motion equation is considered within a level set formulation, can deal with topological changes and important shape deformations. An efficient numerical schema is used for the flow implementation that exhibits robust behavior and has fast convergence rate. Promising results on real and synthetic images demonstrate the potentials of the flow.
  • Keywords
    differential geometry; edge detection; image segmentation; boundary extraction; convergence rate; edge driven bidirectional geometric flow; geodesic active contour flow; gradient vector flow; motion equation; shape deformation; synthetic images; topological changes; Active contours; Computer vision; Deformable models; Equations; Image segmentation; Lagrangian functions; Level set; Shape; Solid modeling; Topology; Algorithms; Artificial Intelligence; Computer Graphics; Image Enhancement; Image Interpretation, Computer-Assisted; Information Storage and Retrieval; Numerical Analysis, Computer-Assisted; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted; Subtraction Technique;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/TPAMI.2004.1262337
  • Filename
    1262337