Generate a New Types of Fuzzy $$ \Psi _{i} $$-Operator

Abstract

In recent years, fuzzy set technology has become a serious element in the field of computer vision and artificial intelligence. As a consequence of intensive research activity, it now competes with classical methods in terms of quality and performance. This mathematical branch has been shown to be very useful in modeling several problems which arise in branches of applied sciences such as Economics, Artificial Intelligence, and Computer Science. An example in that last field is its role in image processing, where a fuzzy operator is used to solve image processing problems such as image smoothing, extracting edges, sharpening images. The aim of this research is to introduce different types of fuzzy operators that help programmers to solve the problems of image processing, encryption or communication. We provided four types of the fuzzy $$ \Psi $$-operators based on the definition of fuzzy local functions and study of the advantages and differences between them. We also, introduced different types of fuzzy topology that are easy to handle in processing programs to help specify the properties of digital images.