A fuzzy expert system for low level image segmentation

In this paper a general purpose fuzzy expert system is presented for low level image segmentation. By means of approximate reasoning based on fuzzy logic, the criticality of the choice of the several thresholds and parameters which usually must be tuned to make the expert system work properly is reduced. More specifically, it is proved that, by keeping constant the number of rules the expert system consists of, the fuzzy approach permits to build a more general system, capable of giving satisfactory results for a large number of images stemming from different applications. The validity of the approach is demonstrated by comparing the effectiveness of a classical expert system with that of its corresponding fuzzy version. Upon analysis of the results, the superiority of the fuzzy system in terms of robustness and generality comes out.