• DocumentCode
    2473028
  • Title

    Force histograms computed in O(NlogN)

  • Author

    Ni, JingBo ; Matsakis, Pascal

  • Author_Institution
    Univ. of Guelph, Guelph, ON, Canada
  • fYear
    2008
  • fDate
    8-11 Dec. 2008
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    The relative position between two objects in a 2D raster image is often represented quantitatively by a force histogram. In the general case, force histograms are computed in O(KN¿N) time: N is the number of pixels in the image and K is the number of directions in which forces are considered. When the objects are defined as fuzzy sets, this complexity also depends quadratically on the number M of possible membership degrees. In the present paper, an algorithm that runs in O(NlogN) is introduced. Computation times are basically independent of K and M. All objects (convex, concave, crisp, fuzzy) are handled in an equally fast manner. Experiments validate the theoretical analysis.
  • Keywords
    computational complexity; fuzzy set theory; image representation; 2D raster image; force histograms; fuzzy sets; Biomedical imaging; Cranium; Fast Fourier transforms; Fuzzy sets; Geographic Information Systems; Histograms; Image databases; Indexing; Layout; Pixel;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2008. ICPR 2008. 19th International Conference on
  • Conference_Location
    Tampa, FL
  • ISSN
    1051-4651
  • Print_ISBN
    978-1-4244-2174-9
  • Electronic_ISBN
    1051-4651
  • Type

    conf

  • DOI
    10.1109/ICPR.2008.4761010
  • Filename
    4761010