Real-Time Traffic Light Control System Based on Background Updating and Edge Detection

Traffic congestion at intersections is one of the most problems encountered by the population in large cities. Shutdowns and delays in traffic light consume fuel and increase the vehicle's travel time and greenhouse gas emissions. Therefore, an effective traffic control system can minimize shutdowns and delays at traffic lights. In this paper, an image processing system in real time has been proposed to measure the density of traffic to adjust the timing of the traffic light. The method proposed here is based on applying the combination of background updating and edge detection to separate the edges of vehicles from the edges of the objects of the background (e.g., marks on the road or shadows of trees or building). The algorithm is applied to videos obtained by stationary cameras.