• DocumentCode
    1544964
  • Title

    Image Segmentation Using Active Contours With Normally Biased GVF External Force

  • Author

    Wang, Yuanquan ; Liu, Lixiong ; Zhang, Hua ; Cao, Zuoliang ; Lu, Shaopei

  • Author_Institution
    Beijing Lab. of Intell. Inf. Technol., Beijing Inst. of Technol. (BIT), Beijing, China
  • Volume
    17
  • Issue
    10
  • fYear
    2010
  • Firstpage
    875
  • Lastpage
    878
  • Abstract
    Gradient vector flow (GVF) is an effective external force for active contours, but its isotropic nature handicaps its performance. The recently proposed NGVF model is anisotropic since it only keeps the diffusion along the normal direction of the isophotes; however, it is sensitive to noise and could erase weak boundaries. In this letter, the normally biased GVF (NBGVF) external force is proposed for snake models, which keeps the diffusion along the tangential direction of the isophotes and biases that along the normal direction. The biasing weight approaches zero at boundaries and is 1 in homogeneous regions. Consequently, the NBGVF snake can preserve weak edges and smooth out noise while maintaining other desirable properties of GVF and NGVF snakes such as enlarged capture range, insensitivity to initialization and convergence to u-shape concavity. These properties are evaluated on synthetic and real images.
  • Keywords
    gradient methods; image segmentation; NBGVF external force; NGVF model; active contours; gradient vector flow; image segmentation; normally biased GVF external force; u-shape concavity; Active contours; Anisotropic magnetoresistance; Convergence; Educational technology; Image restoration; Image segmentation; Information technology; Level set; Partial response channels; Solid modeling; Active contour; NGVF; gradient vector flow; image segmentation; normally biased gradient vector flow;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1070-9908
  • Type

    jour

  • DOI
    10.1109/LSP.2010.2060482
  • Filename
    5518389