Apply driving assistance system to vehicles can significantly reduce accidences and thus attracts much interest nowadays. However, most existing systems are designed specifically for small vehicles and always suffer from drawbacks such as low pedestrian and vehicle detection accuracy and long detection time. To solve these issues, in this paper we develop a driver assistance system based on radar and camera, which can be applied to large vehicles and can detect vehicle and pedestrian simultaneously. Specifically, we combine the image subtraction technique and histogram algorithm to perform pedestrian and vehicle detection to improve detection rate. What’s more, this system can automatically determine whether the object is inside a danger region. If yes, an associated warning signal will be triggered to alarm the driver. Experimental results show that the successful detection rate is sufficiently good and the detecting speed is fast enough to timely alarm the driver to avoid accidents.
Vision-based vehicle detection for a driver assistance system