Unmanned aerial vehicles (UAVs) are becoming more predominant in modern reconnaissance in both military and civilian applications. Object identification and tracking are typical elements of most missions. While large and expensive UAVs operate in many theatres, there is a need for local intelligence gathering using small, low cost and often disposable UAV platforms. In many situations it may not be practical or desirable for the UAV to be relaying information to the ground via radio link. Similarly, waiting upon ground based control for instruction may also limit the usefulness of a UAV. While ground based control is common, full autonomy allows a UAV to operate beyond the range of human intervention. In such cases, the UAV must be capable of making decisions for itself based on information gained from its surroundings. This paper discusses the development of a vision processing system for a low-cost UAV with a total flying weight of under 3 kg. The system has currently been tested using simulated and real aerial footage with a mission to detect the presence of cars and land vehicles in the field of view. Experiments were conducted using actual FPGA based hardware. This research was conducted by Ashiri and Pyke as part of an undergraduate thesis project in the Dept. Electrical and Computer Systems Engineering at Monash University