• DocumentCode
    698737
  • Title

    Category pruning in image databases using segmentation and distance maps

  • Author

    Sumengen, Baris ; Manjunath, B.S.

  • Author_Institution
    ECE Dept., UC, Santa Barbara, CA, USA
  • fYear
    2005
  • fDate
    4-8 Sept. 2005
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    A novel framework for pruning a category of images is proposed in this paper. We assume no prior information about the contents or semantics of the images. Our framework discovers consistencies and knowledge about the spatial relations of the categories unsupervised using iterative image segmentation and spatial grouping. A measure for deciding how well an image fits to a category is proposed and the effectiveness of this measure is investigated.
  • Keywords
    data mining; image segmentation; iterative methods; visual databases; category pruning; distance maps; image databases; iterative image segmentation; knowledge discovery; spatial grouping; spatial relations; Histograms; Image color analysis; Image databases; Image segmentation; Satellites; Semantics; Web sites;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing Conference, 2005 13th European
  • Conference_Location
    Antalya
  • Print_ISBN
    978-160-4238-21-1
  • Type

    conf

  • Filename
    7078331