Automatic vehicle speed estimation method for unmanned aerial vehicle images

This paper presents a solution to solve the detection and estimating the speed problem for road vehicles in images acquired by means of unmanned aerial vehicles (UAVs). UAV photographing which can conveniently take vehicles picture and save time for setting up fixed cameras have become an important part of the intelligent transportation system (ITS). UAV images are characterized by a very high spatial resolution (order of a few centimeters), and consequently by an extremely high level of details which call for appropriate automatic analysis methods. The proposed method starts with the hue, saturation, and value (HSV) color space transformation in order to reduce the influence of light change, and uses the saturation features to remove shadows in the aerial images. Then, it performs a temporal difference process to separate moving objects (vehicles) and backgrounds. The last step of our method is focused on finding out the centroid of vehicles and the moving distance expressed in pixels, and in the end the road lane is used as a scale to estimate the speed of vehicles. The experimental results show that this method performs well in 20 meters to 40 meters in height, and the vehicle speed calculation error is less than 3.47%.