Fingerprint recognition based on adaptive neuro-fuzzy inference system

Abstract

Fuzzy logic (FL) is a powerful problem solving methodology receiving wide spread acceptance for a range of applications. FL is also considered for image understanding applications such as edge detection, feature extraction, classification and clustering. It provides a simple and easy way to draw a definite conclusion from ambiguous, imprecise or vague information. Like Artificial Neural Network (ANN) models, some fuzzy inference system (FIS)s have the capability of universal approximation. The adaptive neuro-fuzzy inference system (ANFIS) belongs to the class of systems commonly known as neuro-fuzzy systems (NFs). NFs combines the advantages of ANN with those of fuzzy systems. An ANFIS based identification system is described here which uses fingerprint as an input. Experiments are carried out using a number of samples. Obtained results show that the system is reliable enough for considering it as a part of a verification mechanism. © Springer-Verlag 2013.