The British Machine Vision Association and Society for Pattern Recognition 

BibTeX entry

  AUTHOR={Olly Oechsle},
  TITLE={Towards the Automatic Construction of Machine Vision Systems
    using Genetic Programming},
  SCHOOL={University of Essex},


Computer vision is a topic that has interested researchers and commercial organisations alike for some time: it provides both a considerable intellectual challenge, and a wide variety of useful applications, some of which are now becoming ubiquitous. In this thesis the author has studied means by which vision software may be constructed automatically using Genetic Programming (GP) – a technique that learns how to write programs during a simulation of Darwinian evolution. This research addresses the question of how one might create more “complete” vision systems using GP, beyond simply proving the applicability of evolutionary learning to particular image processing tasks. Research into making Genetic Programming more suitable for deployment as a generic learning tool is presented, evaluated and assessed, and novel means by which multi-stage vision systems can be constructed from evolved components is described. The author does not claim to have invented significant new paradigms in either GP or mainstream computer vision – rather the focus is on bridging the gap between task-specific applications and a generic learning framework. An architecture for creating such applications is presented, along with software that permits non-expert users to create vision systems rapidly of a complexity first equal to, then beyond that so far published by GP researchers.