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Typical problems concerning to Digital Image Processing (DIP) and to Digital Signals Processing require specific models for each particular problem and the characteristics of the data involved. However, usually these data show a high degree of uncertainty due to the acquisition system itself, noise or uncertainties related to the nature of the problem. They often require considering different points of view of experts in a single model to determine a set of rules or predicates that would achieve the desired solution. Type-2 fuzzy sets can adequately model such uncertainties. This paper presents a study on different applications of type-2 fuzzy sets in image and signal processing, analyzing the main advantages of this type of fuzzy sets in modeling uncertainties. We also review the definitions of type-2 fuzzy sets, their main properties and operations between them.

A survey of medical images and signal processing problems solved successfully by the application of Type-2 Fuzzy Logic