[[alternative]]Vision-Based Traffic Measurement System

[[abstract]]In this paper, a vision-based traffic measurement system is addressed. The objective of this system is twofold, automatically count the vehicles passing through a roadway and measure their speeds. The collected data will be used to compute a number of traffic parameters, including flow rate, demand, time headway, throughput, mean speed, and density. This system consists of one off-line module (preprocessing) and three on-line modules (vehicle detection, vehicle tracking, and calculation of traffic parameters). In the preprocessing component, four off-line tasks are performed, background image generation, lane detection, vanishing point detection, and camera calibration. The background image is used by the vehicle detection module to quickly extract foreground objects from video images through image subtraction. Foreground objects are tracked across the video sequence by the tracking module. Once the traces of vehicles are determined, the trace count gives the number of vehicles. The 2D traces are converted into 3D ones using the transformation functions determined during camera calibration. The speeds of vehicles are then calculated. Based on the number of vehicles and their speeds, the desired traffic parameters are computed. We present the results of some experiments using real image sequences made using a home video camera and a traffic surveillance system. Finally our conclusions show that our proposed system is both adaptable and accurate.