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The present chapter deals with the application of Fuzzy Inference Systems (FIS) for the classification of images, once they have been pre-processed through suitable algorithms. One of the main reasons for exploiting a FIS to this aim lies in the possibility of approaching the problem in a way similar to human reasoning. In fact a FIS allows:  To describe the problem in linguistic terms;  To translate the human experience (which is very often the reference starting point in industrial applications) through inference rules. The possibility of providing a methodological description in linguistic terms is a great advantage in problems that cannot be solved in terms of precise numerical relations, especially when only empirical a priori knowledge is available.  To perform an eventual further adaptation of the rules of the inference machine by exploiting the available data, as a neural training algorithm can be applied to tune some parameters of the fuzzy classifier.

Fuzzy Inference Systems Applied to Image Classification in the Industrial Field