Research Article
Moving cast shadow elimination based on luminance and texture features for traffic flow
@INPROCEEDINGS{10.4108/chinacom.2010.68, author={Liang Gao and Jianping Xing and Hui Li and Yongzhi Wang and Lina Zheng and Xiling Luo}, title={Moving cast shadow elimination based on luminance and texture features for traffic flow}, proceedings={5th International ICST Conference on Communications and Networking in China}, publisher={IEEE}, proceedings_a={CHINACOM}, year={2011}, month={1}, keywords={Gaussian Mixture Model moving cast shadow detection CIE Luv color space texture analysis}, doi={10.4108/chinacom.2010.68} }- Liang Gao
Jianping Xing
Hui Li
Yongzhi Wang
Lina Zheng
Xiling Luo
Year: 2011
Moving cast shadow elimination based on luminance and texture features for traffic flow
CHINACOM
ICST
DOI: 10.4108/chinacom.2010.68
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.
