• DocumentCode
    3128558
  • Title

    Mean shift analysis and applications

  • Author

    Comaniciu, Dorin ; Meer, Peter

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Rutgers Univ., Piscataway, NJ, USA
  • Volume
    2
  • fYear
    1999
  • fDate
    1999
  • Firstpage
    1197
  • Abstract
    A nonparametric estimator of density gradient, the mean shift, is employed in the joint, spatial-range (value) domain of gray level and color images for discontinuity preserving filtering and image segmentation. Properties of the mean shift are reviewed and its convergence on lattices is proven. The proposed filtering method associates with each pixel in the image the closest local mode in the density distribution of the joint domain. Segmentation into a piecewise constant structure requires only one more step, fusion of the regions associated with nearby modes. The proposed technique has two parameters controlling the resolution in the spatial and range domains. Since convergence is guaranteed, the technique does not require the intervention of the user to stop the filtering at the desired image quality. Several examples, for gray and color images, show the versatility of the method and compare favorably with results described in the literature for the same images
  • Keywords
    computer vision; image segmentation; color images; density gradient; discontinuity preserving filtering; gray level; image segmentation; lattices; mean shift analysis; nonparametric estimator; spatial-range domain; Application software; Color; Computer vision; Convergence; Image quality; Image segmentation; Kernel; Lattices; Pixel; Spatial resolution;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision, 1999. The Proceedings of the Seventh IEEE International Conference on
  • Conference_Location
    Kerkyra
  • Print_ISBN
    0-7695-0164-8
  • Type

    conf

  • DOI
    10.1109/ICCV.1999.790416
  • Filename
    790416