Fuzzy granulation in image processing using fuzzy linguistic rules. Application to a fuzzy reasoning edge detector

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 t...

Full description

Saved in:
Bibliographic Details
Main Authors: Bombardier, V., Voisin, A., Levrat, E.
Format: Conference Proceeding
Language:English
Subjects:
Detectors
Fuzzy logic
Fuzzy reasoning
Fuzzy set theory
Fuzzy sets
Fuzzy systems
Image edge detection
Image processing
Image segmentation
Neutron spin echo
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
DOI:10.1109/FUZZ.2001.1007315