Vehicle Movement Tracking and Control Using Image Processing

This paper proposes machine vision-based live traffic monitoring aided with various image processing methods. The application is designed to monitor live traffic on a road or private property premises with features like vehicle counting, incoming and outgoing vehicle counting, speed estimation, so that the results can aid intelligent traffic management. Typical image processing tools like thresholding, canny edge, DeepSORT, Kalman filter, and Hungarian algorithm are used for the purpose. Vehicle detection accuracy of 94.8% and counting accuracy of 86.6% are achieved. Based on the traffic density, green for good to go and red for stop indications are also included.