Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal International Journal of Quantitative Research and Modeling
Oluwakemi C. Abikoye
Department of Computer Science, University of Ilorin, Ilorin
Computer Science & IT Decision Sciences, Operations Research & Management Engineering Environmental Science Physics

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
A CNN-Based Bimodal Biometric Authentication System Using Face and Iris Recognition Oluwakemi C. Abikoye; Ridwan Opeyemi Kasope; Kafayat Odunayo Tajudeen; Abimbola Ganiyat Akintola
International Journal of Quantitative Research and Modeling Vol. 7 No. 2 (2026): International Journal of Quantitative Research and Modeling (IJQRM)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v7i2.1318

Abstract

In the evolving landscape of information technology, this study presents a bimodal biometric authentication system that combines facial and iris recognition using advanced Convolutional Neural Networks (CNNs) to address the escalating security concerns of personal and sensitive information. The bimodal approach leverages the unique textures of facial and iris features to create a robust and secure authentication mechanism, demonstrating high accuracy (95.76%) and precision value of 97.83%, low False Acceptance Rate (2.54%) and False Rejection Rate (14.29%). The system framework integrates the strengths of both facial and iris modalities, mitigating vulnerabilities inherent in unimodal systems and advancing the field of biometric authentication by providing a resilient solution against emerging cyber threats, enhancing the reliability of user identification, and contributing to safer digital environments across various domains.
Co-Authors Abimbola Ganiyat Akintola Kafayat Odunayo Tajudeen Ridwan Opeyemi Kasope