Fuzzy granulation in image processing using fuzzy linguistic rules. Application to a fuzzy reasoning edge detector
Vincent Bombardier, Alexandre Voisin, Éric Levrat · 2002
This article presents a survey of the use of fuzzy set theory in the image processing from which we obtain a formalism. In this formalism, we defined a general structure applicable to various fuzzy approaches and especially in edge detection. We develop a fuzzy rule approach under which we analyze the construction of the contextual model or knowledge base. This model is constructed through the theory of the fuzzy granulation information (TFGI). Therefore, we use the TFGI, in order to include linguistic information known as high level in a low level processing. Thus, we aim to make low level processing "context dependent". We apply our model in a fuzzy reasoning edge detection operator.