Image analysis is one of the most interesting ways for a mobile vehicle to understand its environment. One of the tasks of an autonomous vehicle is to get accurate information of what it has in front, to avoid collision or find a way to a target. This task requires real-time restrictions depending on the vehicle speed and external object movement. The use of normal cameras, with homogeneous (squared) pixel distribution, for real-time image processing, usually requires high performance computing and high image rates. A different approach makes use of a CMOS space-variant camera that yields a high frame rate with low data bandwidth. The camera also performs the log-polar transform, simplifying some image processing algorithms. One of this simplified algorithms is the time to impact computation. The calculation of the time to impact uses a differential algorithm. A pipelined architecture specially suited for differential image processing algorithms has been also developed using programmable FPGAs.
['Fernando Pardo', 'Isaac Llorens', 'Francisco Micó', 'Jose Antonio Boluda']
Space variant vision and pipelined architecture for time to impact computation