Abstract: Now a days, road accidents and traffic issues are on the rise. Video-based vehicle detection technology can gather valuable data from video frames, like vehicle speed, type and license plates cost effectively and efficiently. This data can improve traffic management and enhance safety. Traditional speed detection systems still rely on traditional algorithms like YOLOv5 and SSD that lack in accuracy. Our proposed system uses cutting-edge technologies in machine learning and video steaming analysis. The system integrates YOLOv8 for precise vehicle detection, DeepSORT for robust tracking of vehicles, and EasyOCR in conjunction with YOLOv8 for accurate license plate number detection. On detecting the vehicle the speed of each vehicle is estimated and it’s details are noted upon speed violation. Integration of these technologies improves traffic monitoring and reduces road accidents. The data collecting by these can later be used for alerting the drivers and as well as control teams.
Keywords: Vehicle detection, tracking, Vehicle speed detection, video streaming analysis, DeepSORT, YOLOv8 EasyOCR.
|
DOI:
10.17148/IJARCCE.2024.13442
