A surveillance system including digital (ultra) High-Definition Video (HDV) cameras deployed for monitoring and reporting incidences of traffic violations is constantly longing. The camera arrangement is coupled to a data processing system, which encompasses an image processor for compiling vehicle and scene images produced by the digital cameras. There will be a verification process to corroborate the validity of the vehicle images, an image processing system for identifying the vehicle and driver information, as well as a notification procedure for transferring the potential infringement information to a Law Enforcement Agency (LEA). In parallel, the video camera system is configured to record the footage both before and after the moment the offense being detected. The resulting video is consequently incorporated with the conventional evidence set comprising the digital still images of the offense to pinpoint the data of the vehicle and the driver. In this research, we develop such system that uses Computer Vision (CV) to identify traffic violations, such as over-speeding, illegal parking, or wrong-way driving. After identifying and detecting the infraction, the system may extract the characters from the violating vehicle’s license plate, and generate later the fine ticket. The system will be built with the YOLO model for recognizing the traffic offenses and the EasyOCR package for extracting the information from the license plates.


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    Titel :

    Automated Traffic Violation Monitoring and Reporting System


    Weitere Titelangaben:

    Lect. Notes on Data Eng. and Comms.Technol.


    Beteiligte:
    Dao, Nhu-Ngoc (Herausgeber:in) / Pham, Quang-Dung (Herausgeber:in) / Cho, Sungrae (Herausgeber:in) / Nguyen, Ngoc Thanh (Herausgeber:in) / Nguyen, Hao Xuan (Autor:in) / Nguyen, Minh N. T. (Autor:in)

    Kongress:

    International Conference on Intelligence of Things ; 2024 ; Da Nang, Vietnam September 12, 2024 - September 14, 2024



    Erscheinungsdatum :

    17.12.2024


    Format / Umfang :

    11 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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