Fuzzy reasoning rule-based system for image segmentation
Z. Hamrouni, Charlie J. Krey, Alain Ayache · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1990
This paper introduces a general purpose method for black and white image segmentation, which is based on the design of a rule based-system. Rules integrate general knowledge, which is completely independent of environment and scene content ; they process simultanuously regions and lines by merging similar regions, splitting non uniform ones, connecting lines or deleting non significant ones. Rules are selected according to the nature of data under analysis, evaluated by means of a set of performance measurement and ordered according to their efficiency ; only the most efficient ones are really fired. Furthermore, adapted control strategies, using dynamic data selection, allow to focuse the process on the required parts of the image. This paper describes some examples of the rule, and the set of performance measurement for rule efficiency evaluation.