Fuzzy Inference Systems Applied to Image Classification in the Industrial Field

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.

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