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
Link To Document :
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