Modular Neural Networks and Type-2 Fuzzy Logic for Face Recognition

Abstract

In this paper we present a method for face recognition combining modular neural networks and two interval type-2 fuzzy inference systems (FIS 2) for face recognition. The first FIS 2 is used for edges detection in the training data, and the second one to find the ideal parameters for the Sugeno integral as a decision operator. Fuzzy logic is shown to be a tool that can help improve the results of a neural system facilitating the representation of the human perception.