• DocumentCode
    1642219
  • Title

    Object segmentation using graph cuts based active contours

  • Author

    Xu, Ning ; Bansal, Ravi ; Ahuja, Narendra

  • Author_Institution
    Univ. of Illinois, Urbana, IL, USA
  • Volume
    2
  • fYear
    2003
  • fDate
    6/25/1905 12:00:00 AM
  • Abstract
    In this paper we present a graph cuts based active contours (GCBAC) approach to object segmentation problems. Our method is a combination of active contours and the optimization tool of graph cuts and differs fundamentally from traditional active contours in that it uses graph cuts to iteratively deform the contour. Consequently, it has the following advantages. (1) It has the ability to jump over local minima and provide a more global result. (2) Graph cuts guarantee continuity and lead to smooth contours free of self-crossing and uneven spacing problems. Therefore, the internal force, which is commonly used in traditional energy functions to control the smoothness, is no longer needed, and hence the number of parameters is greatly reduced. (3). Our approach easily extends to the segmentation of three and higher dimensional objects. In addition, the algorithm is suitable for interactive correction and is shown to always converge. Experimental results and analyses are provided.
  • Keywords
    graph theory; image segmentation; minimisation; object recognition; stereo image processing; energy function; energy minimization; graph cuts based active contour method; interactive correction; iterative contour deformation; local minima; object segmentation; optimization; parameter reduction; self-crossing problem; smooth contour; uneven spacing problem; Active contours; Automatic control; Background noise; Computer vision; Force control; Image segmentation; Object segmentation; Optimization methods; Psychiatry; Robust stability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition, 2003. Proceedings. 2003 IEEE Computer Society Conference on
  • ISSN
    1063-6919
  • Print_ISBN
    0-7695-1900-8
  • Type

    conf

  • DOI
    10.1109/CVPR.2003.1211451
  • Filename
    1211451