• DocumentCode
    538428
  • Title

    Moving cast shadow elimination based on luminance and texture features for traffic flow

  • Author

    Gao, Liang ; Xing, Jianping ; Li, Hui ; Wang, Yongzhi ; Zheng, Lina ; Luo, Xiling

  • Author_Institution
    Sch. of Inf. Sci. & Eng., Shandong Univ., Jinan, China
  • fYear
    2010
  • fDate
    25-27 Aug. 2010
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    A new algorithm namely moving cast shadow elimination based on luminance and texture features (MSELT) to detect moving shadows of vehicles is investigated in this paper. Different from traditional methods only performed in color space, we combine the luminance in the CIE Luv color space and texture feature to determine shadows. The proposed algorithm based on Gaussian Mixture Model (GMM) uses the luminance weight in the CIE Luv color space to model background, do texture analysis and detect shadows. Texture analysis is performed by evaluating the gradients in the foreground with the observation that shadow regions present smooth texture characteristics. The experimental results show that this method outperforms results obtained with color space information alone, particularly in detection of vehicles which present similar luminance characteristics with shadows.
  • Keywords
    Gaussian processes; computer vision; feature extraction; image colour analysis; image texture; traffic engineering computing; CIE Luv color space; GMM; Gaussian mixture model; MSELT; luminance features; luminance weight; moving cast shadow elimination; texture characteristics; texture features; traffic flow; Adaptation model; Algorithm design and analysis; Color; Gaussian distribution; Image color analysis; Pixel; Vehicles; CIE Luv color space; Gaussian Mixture Model; moving cast shadow detection; texture analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications and Networking in China (CHINACOM), 2010 5th International ICST Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    973-963-9799-97-4
  • Type

    conf

  • Filename
    5684646