• DocumentCode
    2232817
  • Title

    Ellipsoidal Method for Shadow Detection Based on Normalized RGB Values

  • Author

    Junxiang, Gao ; Yan, Tian ; Yong, Liu

  • Author_Institution
    Sch. of Inf. & Commun. Eng., Beijing Univ. of Posts & Telecommun., Beijing
  • Volume
    1
  • fYear
    2009
  • fDate
    30-31 May 2009
  • Firstpage
    104
  • Lastpage
    107
  • Abstract
    This paper presents a new approach of foreground and shadow segmentation in visual surveillance environment. Coordinate systems are firstly defined based on normalized RGB values, and then an ellipsoid is constructed according to scattering feature of shadow pixels. Consequently, moving shadow detection is treated as a clustering problem in above coordinate systems, and all the pixels inside the ellipsoid are extracted as potential shadow pixels. Finally, post-processing is further performed by using the geometrical properties of shadow to verify and confirm pixels classified as shadows in previous step. Experimental results validate the algorithm on a suite of indoor and outdoor video sequences. The performance of the method is markedly higher than that of the two well-known moving shadow detection methods, especially under changing illumination conditions.
  • Keywords
    image resolution; image segmentation; image sequences; video surveillance; clustering problem; ellipsoidal method; foreground segmentation; normalized RGB values; shadow detection; shadow pixels; shadow segmentation; video sequences; visual surveillance; Clustering algorithms; Electronic mail; Ellipsoids; Lighting; Niobium; Scattering; Shape; Smart pixels; Video sequences; Video surveillance; intelligent video surveillance; moving shadow detection; pattern recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Networking and Digital Society, 2009. ICNDS '09. International Conference on
  • Conference_Location
    Guiyang, Guizhou
  • Print_ISBN
    978-0-7695-3635-4
  • Type

    conf

  • DOI
    10.1109/ICNDS.2009.32
  • Filename
    5116222