Iris Biometric Identification Using Artificial Neural Networks

<p>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.</p>

Name thesis:degree_name

MS in Electrical Engineering

Discipline thesis:degree_discipline

Electrical Engineering

Year dc:date.available

2018

Author dc:creator

• Haskett, Kevin Joseph

Contributors dc:contributor

• Xiao-Hua Yu

• Neural Networks
• Eigen Analysis
• Discrete Cosine Transform
• Wavelet Transform
• Classifier
• Iris Identification
• Other Electrical and Computer Engineering

Identifier

10.15368/theses.2018.111

OAI identifier oai:identifier

oai:digitalcommons.calpoly.edu:theses-3281