Artificial Intelligence for Communications and Networks. Second EAI International Conference, AICON 2020, Virtual Event, December 19-20, 2020, Proceedings

Research Article

An Overspeed Capture System Based on Radar Speed Measurement and Vehicle Recognition

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  • @INPROCEEDINGS{10.1007/978-3-030-69066-3_39,
        author={Long Bai and Jiayi Yang and Jie Wang and Mingfeng Lu},
        title={An Overspeed Capture System Based on Radar Speed Measurement and Vehicle Recognition},
        proceedings={Artificial Intelligence for Communications and Networks. Second EAI International Conference, AICON 2020, Virtual Event, December 19-20, 2020, Proceedings},
        proceedings_a={AICON},
        year={2021},
        month={7},
        keywords={Overspeed Speed measurement License plate recognition Photographing},
        doi={10.1007/978-3-030-69066-3_39}
    }
    
  • Long Bai
    Jiayi Yang
    Jie Wang
    Mingfeng Lu
    Year: 2021
    An Overspeed Capture System Based on Radar Speed Measurement and Vehicle Recognition
    AICON
    Springer
    DOI: 10.1007/978-3-030-69066-3_39
Long Bai1, Jiayi Yang1, Jie Wang1, Mingfeng Lu1
  • 1: Beijing Institute of Technology

Abstract

Overspeed has always been a very dangerous behavior for people. This may cause a variety of bad consequences such as car accidents and casualties. We need to be able to obtain the relevant information of the car while detecting the speeding now, so that subsequent punishments can be made, otherwise the perpetrators may commit the crime again. This paper proposes a high-precision, efficient method for taking photos of speeding vehicles and vehicle recognition. We directly connect the radar speed measurement module with the camera module, so that we only have one terminal for the whole system. When the radar module detects that the vehicle is speeding, it will send it directly to the camera module, so that it can capture the overspeed vehicle. This accelerates the response speed of the camera module. Therefore, when we design imaging devices, we can lower the requirements without reducing the accuracy. We can timely capture the image even if we choose the camera with low price and low quality. At last, we use image processing and support vector machines to identify the license plate. The whole system has not much equipment and can be installed in a narrow space.