Abstract
Video-based moving vehicle detection is an important prerequisite for vehicle tracking and vehicle counting. However, in the natural scene, the conventional optical flow method cannot accurately detect the boundary of the moving vehicle due to the generation of the shadow. In order to solve this problem, this paper proposes an improved moving vehicle detection algorithm based on optical flow method and shadow removal. The proposed method firstly uses the optical flow method to roughly detect the moving vehicle, and then uses the shadow detection algorithm based on the HSV color space to mark the shadow position after threshold segmentation, and further combines the region-labeling algorithm to realize the shadow removal and accurately detect the moving vehicle. Experiments are carried out in complex traffic scenes with shadow interference. The experimental results show that the proposed method can well solve the impact of shadow interference on moving vehicle detection and realize real-time and accurate detection of moving vehicles.
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Acknowledgement
This work is supported in part by the National Nature Science Foundation of China (No. 61304205, 61502240), Natural Science Foundation of Jiangsu Province (BK20191401), and Innovation and Entrepreneurship Training Project of College Students (201910300050Z, 201910300222).
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© 2020 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Sun, M., Sun, W., Zhang, X., Zhu, Z., Li, M. (2020). Moving Vehicle Detection Based on Optical Flow Method and Shadow Removal. In: Zhang, X., Liu, G., Qiu, M., Xiang, W., Huang, T. (eds) Cloud Computing, Smart Grid and Innovative Frontiers in Telecommunications. CloudComp SmartGift 2019 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 322. Springer, Cham. https://doi.org/10.1007/978-3-030-48513-9_36
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DOI: https://doi.org/10.1007/978-3-030-48513-9_36
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