• DocumentCode
    507321
  • Title

    Multiscale Cascade Segmentation of Deformable Image and Parameters Evaluation

  • Author

    Xiang, Long ; Tao, Zhang

  • Author_Institution
    Dept. of Electron. Inf. Eng., Hainan Univ., Haikou, China
  • Volume
    5
  • fYear
    2009
  • fDate
    14-16 Aug. 2009
  • Firstpage
    405
  • Lastpage
    409
  • Abstract
    Methods based on deformable model have been widely used in deformable image segmentation. The segmentation quality of this kind of methods strongly relies on its initialization. If the initiation isn´t accurate, the segmentation result will not be satisfactory. To solve this problem, we propose a new deformable image cascade segmentation method. In the method, the MSRF and SMAP will be used to estimate motion parameters of the background of image sequence. From the result of simulation, we can conclude that the segmentation method is satisfactory.
  • Keywords
    image segmentation; parameter estimation; deformable image segmentation; motion parameter estimation; multiscale cascade segmentation; parameter evaluation; Cameras; Deformable models; Educational institutions; Fuzzy systems; Image segmentation; Image sequences; Information science; Knowledge engineering; Motion estimation; Potential energy; Multiscale Random Field; cascade segmentation; global motion; snake model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09. Sixth International Conference on
  • Conference_Location
    Tianjin
  • Print_ISBN
    978-0-7695-3735-1
  • Type

    conf

  • DOI
    10.1109/FSKD.2009.82
  • Filename
    5360588