• DocumentCode
    2828227
  • Title

    Tensor vector field based active contours

  • Author

    Kumar, Abhishek ; Wong, Alexander ; Mishra, Akshaya ; Clausi, David A. ; Fieguth, Paul

  • Author_Institution
    Dept. of Syst. Design Eng., Univ. of Waterloo, Waterloo, ON, Canada
  • fYear
    2011
  • fDate
    11-14 Sept. 2011
  • Firstpage
    2833
  • Lastpage
    2836
  • Abstract
    Among the main limitations of active contours are their high noise sensitivity and poor capture range from the target object. One of the most promising approaches for addressing these limitations is the concept of Vector Field Convolution (VFC). However, due to its isotropic vector field kernel, VFC does not take full advantage of the underlying image structural characteristics. By specifically addressing this idea, a novel local tensor vector field approach is developed to adaptively account for these structural characteristics. Experimental results demonstrate that the proposed adaptive method leads to more accurate segmentation.
  • Keywords
    convolution; edge detection; image segmentation; tensors; vectors; adaptive method; image structural characteristics; isotropic vector field kernel; local tensor vector field approach; tensor vector field based active contours; vector field convolution; Active contours; Image segmentation; Kernel; PSNR; Tensile stress; Vectors; Active Contour; Segmentation; Snake; Tensor Vector Field; Vector Field Convolution;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2011 18th IEEE International Conference on
  • Conference_Location
    Brussels
  • ISSN
    1522-4880
  • Print_ISBN
    978-1-4577-1304-0
  • Electronic_ISBN
    1522-4880
  • Type

    conf

  • DOI
    10.1109/ICIP.2011.6116262
  • Filename
    6116262