Abstract
In order to collect real-time vehicle queue length at intersections to determine congestion, further optimize traffic light control duration and alleviate traffic congestion. Integrates the advantages of Canny edge detection operator and proposes a vehicle queue length detection method based on the improvement of Canny edge detection operator. Vehicle motion detection is achieved by the three-frame differential method, vehicle presence detection is performed using a combination of the improved Canny edge detection operator and the background differential method, and then the maximum and minimum values of the vertical coordinates of the queue length in the region of interest (ROI) region of the video image are collected and the transformation from the pixel distance to the actual queue length is completed using the camera calibration technique to achieve queue length detection. The experimental results show that the method can achieve queue length detection, and the improved detection effect is more accurate than before the improvement, and the error is within the allowable range to meet the measurement requirements.
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Li, Z., Yao, Q. (2022). Video Image Processing Based Intersection Vehicle Queue Length Detection. In: Xie, Q., Zhao, L., Li, K., Yadav, A., Wang, L. (eds) Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery. ICNC-FSKD 2021. Lecture Notes on Data Engineering and Communications Technologies, vol 89. Springer, Cham. https://doi.org/10.1007/978-3-030-89698-0_23
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DOI: https://doi.org/10.1007/978-3-030-89698-0_23
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