• DocumentCode
    2867720
  • Title

    Image Segmentation Using Curve Evolution and Anisotropic Diffusion: An Integrated Approach

  • Author

    Pan, Yongsheng ; Birdwell, J. Douglas ; Djouadi, Seddik M.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Tennessee Univ., Knoxville, TN
  • fYear
    2005
  • fDate
    14-14 Dec. 2005
  • Firstpage
    387
  • Lastpage
    394
  • Abstract
    In this paper, a new model is proposed for image segmentation that integrates the curve evolution and anisotropic diffusion methods. The curve evolution method, utilizing both gradient and region information, segments an image into multiple regions. During the evolution of the curve, anisotropic diffusion is adaptively applied to the image to remove noise while preserving boundary information. Coupled partial differential equations (PDE´s) are used to implement the method. Experimental results show that the proposed model is successful for complex images with high noise
  • Keywords
    curve fitting; gradient methods; image segmentation; partial differential equations; anisotropic diffusion method; boundary information; complex image segmentation; coupled partial differential equation; curve evolution method; gradient information; noise removal; region information; Active contours; Active noise reduction; Anisotropic magnetoresistance; Image segmentation; Information technology; Laboratories; Level set; Object detection; Partial differential equations; Solid modeling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia, Seventh IEEE International Symposium on
  • Conference_Location
    Irvine, CA
  • Print_ISBN
    0-7695-2489-3
  • Type

    conf

  • DOI
    10.1109/ISM.2005.68
  • Filename
    1565859