Abstract—Identification of individuals based on behavior or
biology is known as biometrics. A recent and widely used
development in the field of biometrics is iris recognition for
identification. The average iris recognition algorithm requires
taking an image of the iris, then testing and segmenting the
image. This is commonly achieved through both statistical and
classical techniques. Every method has strengths and
weaknesses. In this proposal, we present a novel iris recognition
approach. The objective of our study is to create a technique for
accessing computers and computer networks. Due to
widespread use of computers in many forms (desktop, handheld,
etc.) our technique offers valuable security for information.
This wavelet-based algorithm will be capable of enhancing the
scanned image, reducing noise, and extracting important
elements of the picture to check against data within a database.
Additionally, our method may be generalized to a variety of
applications including surveillance, e-commerce, ATM
transactions, and others.
Index Terms—DCNN, biometrics, multi-resolution transform, wavelet, image fusion.
A. Alshehri is with the Electrical Engineering Department, King Abdulaziz University, Jeddah, KSA (e-mail: firstname.lastname@example.org).
S. Ezekiel and T. Daws are with the Computer Science Department, Indiana University of Pennsylvania, Indiana, PA USA.
Cite: Abdullah Ali Alshehri, Tyler Daws, and Soundararajan Ezekiel, "Iris Biometrics for Secure Authentication," International Journal of Machine Learning and Computing vol. 10, no. 3, pp. 482-489, 2020.Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).