• DocumentCode
    2926351
  • Title

    Objects detection by expectation-maximisation algorithm application to football images

  • Author

    Jlassi, Mourad Moussa ; Douik, Ali ; Messaoud, Hassani

  • Author_Institution
    Ecole Nat. d´´Ing. de Monastir, Monastir, Tunisia
  • fYear
    2009
  • fDate
    5-8 July 2009
  • Firstpage
    317
  • Lastpage
    320
  • Abstract
    In this paper we present a supervised method of image segmentation based on the statistic approach expressed in an hybrid space constituted by the three relevant chromatic level deduced by histogram analysis approach, this technique may the possibility of adapting the treatments to the local context of image with a little priori knowledge. This method has been applied on colour images issued from a soccer video of football sports. The obtained results show how his method reconstructs faithfully the size of different region while discriminating textures areas. We next study the influence of statistical parameters and chromatic level on these results.
  • Keywords
    expectation-maximisation algorithm; image colour analysis; image recognition; image segmentation; image sequences; object detection; chromatic level; colour images; expectation-maximisation algorithm; football images; histogram analysis; image segmentation; object detection; Algorithm design and analysis; Computer vision; Expectation-maximization algorithms; Histograms; Image analysis; Image color analysis; Image segmentation; Object detection; Phase estimation; Statistical analysis; Color; Image segmentation; Image sequence analysis; Statistics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computers and Communications, 2009. ISCC 2009. IEEE Symposium on
  • Conference_Location
    Sousse
  • ISSN
    1530-1346
  • Print_ISBN
    978-1-4244-4672-8
  • Electronic_ISBN
    1530-1346
  • Type

    conf

  • DOI
    10.1109/ISCC.2009.5202315
  • Filename
    5202315