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This thesis presents image processing solutions in FPGA based embedded vision systems. Image processing is a demanding process but the information that can be extracted from images is very useful and can be used for many tasks like mapping and navigation, object detection and recognition, collision detection and more.

Image processing or analysis involves reading images from a camera system, improve an image with respect to colour fidelity and white balance, removing distortion, extracting salient information. The mentioned steps are often referred to as low to medium level image processing and involve large amounts of data and fairly simple algorithms suitable for parallel processing.

Medium to high level processing involves a reduced amount of data and more complex algorithms. Object recognition which involves matching image features to information stored in a database is of higher complexity.

A vision system can be used in anything from a car to industry processes to mobile robots playing soccer or assisting people in their homes. A vision system often works with video streams that are processed to find pieces that can be handled in an industry process, detect obstacles that may be potential hazards in traffic or to find and track landmarks in the environment that can be used to build and navigate from. This involves large amount of calculations and this is a problem, even though modern computers are fast they may still not be able to execute the desired algorithms with the frequency wanted. Even if there are computers that are fast enough they are bulky and require a lot of power. They are not suitable for incorporating on small mobile robots.

In this thesis I will present the image processing sequence to give an understanding of the complexity of the processes involved and I will discuss some processing platforms suitable for image processing. I will also present my work that is focused on image algorithm implementations for reconfigurable hardware suitable for mobile robots with requirements on speed an power consumption.