Iris Biometric Identification Using Artificial Neural Networks

Author

Kevin Joseph Haskett, California Polytechnic State University, San Luis ObispoFollow

DOI: https://doi.org/10.15368/theses.2018.111
Available at: https://digitalcommons.calpoly.edu/theses/1947

Date of Award

8-2018

Degree Name

MS in Electrical Engineering

Department/Program

Electrical Engineering

Advisor

Xiao-Hua Yu

Abstract

A biometric method is a more secure way of personal identification than passwords. This thesis examines the iris as a personal identifier with the use of neural networks as the classifier. A comparison of different feature extraction methods that include the Fourier transform, discrete cosine transform, the eigen analysis method, and the wavelet transform, is performed. The robustness of each method, with respect to distortion and noise, is also studied.