Abstract
In the traffic video scene, the existence of shadows might generate negative effect on pattern analysis. This paper proposes a novel approach which adequately considers color space information to detect moving cast shadows of vehicles in traffic videos. Firstly, RGB component ratios between frame and background as well as blue and red colors ratio (B/R ratio) are taken into account to detect shadows respectively. Then we combine the two results for a refined shadow candidate. Finally, to improve the accuracy of shadow detection, post processing is adopted to correct the false detected pixels. Experimental results on several databases indicate that our approach not only achieves both high shadow detection and discrimination rates but takes on better performance than some state-of-the-art methods.
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Jia, Y., Yu, X., Dai, J., Hu, W., Kong, J., Qi, M. (2013). A Novel Moving Cast Shadow Detection of Vehicles in Traffic Scene. In: Yang, J., Fang, F., Sun, C. (eds) Intelligent Science and Intelligent Data Engineering. IScIDE 2012. Lecture Notes in Computer Science, vol 7751. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36669-7_15
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DOI: https://doi.org/10.1007/978-3-642-36669-7_15
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