A parallel algorithm to extract information about the motion of road traffic using image analysis

Road traffic movement is a very important source of information in traffic management. Although systems exist which can detect the presence of a vehicle and its speed under certain conditions, there is generally a lack of effective means to measure both the speed and direction of traffic movement. This is particularly true for road junctions, where conflicting traffic shares the same space and where some control strategy could be more effectively applied with the help of speed and direction estimates. The increasing use of closed circuit television (CCTV) systems has provided the opportunity to apply image processing techniques to extract such information. However, such techniques are computationally intensive in general, and the application of parallel processing methods is one of the best choices which could bring the desired acquisition of movement information into practical reality. This paper describes a parallel video-based image analysis system which is capable of extracting movement information, including direction and speed, of road vehicular traffic over any part of a road surface. The prototype has been implemented on an array of 36 transputers and an image grabber with a SUN SPARC IPC as the host machine. The software mainly consists of median filtering, feature extraction, spatio-temporal analysis, matching of image features in successive images by neural networks and aggregation of matched results. This algorithm has been tested using data for a signal-controlled junction aiming to capture an opposed turning traffic movement with promising results. It has also been shown that a real-time system based on the described algorithm is feasible. (C) 1997 Elsevier Science Ltd.