Image Processing Algorithms for Driver Assistance using Wide Angle Cameras

Modern vehicles are deployed with a large number of sensors in order to provide a rich spectrum of driver assistance functionality. These systems enhance security and comfort of passengers and other traffic participants alike, but they also pave the road to fully autonomous traffic. In order to provide this functionality robustly and reliably, one currently makes use of numerous specialized sensors: laser, radar, ultrasound, and infrared sensors, as well as different kinds of video cameras. The diversity of sensors comes with high cost and enables complex assistance functions momentarily only for upper-class vehicles. The current research, thus, focuses on the development of better algorithms that make similar systems possible on inexpensive sensors. This thesis examines the aptitude of a new camera system, which has recently grown popular in vehicles of most of the large automobile manufacturers, for all major video-based driver assistance functionality. This so-called Topview system consists of four wide angle cameras with a view angle of up to 200 degrees, usually mounted at the front bumper, the two side mirrors and the trunk lid. By these means, one is able to provide a view surrounding the entire vehicle. However, the single camera images are distorted which substantiates the need for adapted image processing algorithms.