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Cast shadow detection based on the YCbCr color space and topological cuts

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Abstract

In order to solve the moving objects shadow problem in foreground extraction of surveillance video images, a new cast shadow detection algorithm based on the YCbCr color space and topological cutting was proposed. Preliminary shadow removal was first performed based on the difference of the three components in the YCbCr color space of shadows and foregrounds. Besides, the maximum-flow/minimum-cut algorithm for image segmentation was optimized considering the topological constraints. The optimal segmentation of the foreground image was obtained during the continuous updating of the label. Finally, two sets of experiments were performed in video image sequences, including real surveillance videos and a well-known benchmark test set. By comparing with two other existing algorithms, the feasibility and effectiveness of the cast shadow detection algorithm were verified by the smooth border and higher recognition accuracy. In addition, the adaptability to foreground object density and different light intensities was measured in an airport terminal, showing that this algorithm can provide a high quality of moving foreground detection in surveillance video images and can be applied in monitoring of public places.

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Acknowledgements

The authors acknowledge the National Key R&D Program of China (No.2018YFC0809500) and National Natural Science Foundation of China (Grant No.71874081 and No.71573122).

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Authors and Affiliations

  1. College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing, China

    Quan Shao, Chenchen Xu & Yu Zhou

  2. West Air Co. Ltd., Chongqing, China

    Hongji Dong

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  1. Quan Shao
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Correspondence to Quan Shao.

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Shao, Q., Xu, C., Zhou, Y. et al. Cast shadow detection based on the YCbCr color space and topological cuts. J Supercomput 76, 3308–3326 (2020). https://doi.org/10.1007/s11227-018-2558-4

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