Vehicle speed estimation by license plate detection and tracking

We describe a novel system for vehicle speed estimation from videos captured in urban roadways. Our system uses text detection to locate the license plates of passing vehicles, which are then used to select stable features for tracking. The tracked features are then filtered and rectified for perspective distortion. Vehicle speed is estimated by comparing the trajectory of the tracked features to known real world measures. In experiments performed on videos captured under real operation conditions, our system attained a precision of 0.87 and a recall of 0.92 for license plate detection. Vehicle speeds were estimated with an average error of 0.59 km/h, staying inside the +2/-3 km/h limit, determined by regulatory authorities in several countries, in over 75% of the cases.