• Title of article

    Spectral Clustering of Images in LUV Color Space by Spatial-Color Pixel Classification

  • Author/Authors

    C.P. Blesslin Elizabeth، نويسنده , , K. Usha Kingsly Devi، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2010
  • Pages
    5
  • From page
    1
  • To page
    5
  • Abstract
    This work is based on color image segmentation by spatial-color pixel classification in Luv color space. Classes of pixels are difficult to be identified when the color distributions of the different objects highly overlap in the color space and when the color points give rise to non-convex clusters. It is proposed to apply spectral classification to regroup the pixels which represent the same regions, into classes. Spectral clustering achieves a spectral decomposition of a similarity matrix in order to construct an eigen-space in which the clusters are expected to be well separated. The similarity matrix used in this paper is derived from a spatial-color compactness function. This function takes into account both the distribution of colors in the color space and the spatial location of colors in the image plane. Spectral clustering that uses FCM performs better in Luv color space when compared with other Spectral clustering algorithms..
  • Keywords
    Non-convex clusters , Eigen-Space , Spectral clustering
  • Journal title
    International Journal of Computer Applications
  • Serial Year
    2010
  • Journal title
    International Journal of Computer Applications
  • Record number

    659828