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Research Article Open access CC BY 4.0

Combined PCA-Daugman Method : An Effcient Technique for Face and Iris Recognition

Md. Mahbubul Alam, Md. Ashikur Rahman Khan, Zayed Us Salehin, Main Uddin, Sultana Jahan Soheli, Tanvir Zaman Khan

Journal of Advances in Mathematics and Computer Science · pp. 34–44 · Published 27 Jul 2020

10.9734/jamcs/2020/v35i530280

Abstract

Face and iris are very common individual bio-metric features for person identification. Face recognition is the method of identification a person uniquely using face. Principal component analysis is one of the algorithms for face recognition. Iris recognition in another method of person identification using iris. Very popular iris recognition method is Daugman algorithm. Unimodal biometric system has various difficulties to detect a person like noisy and unusual data. Multimodal biometric system combined more than one individual modalities like face and iris to increase the efficiency. In this work, we combined principal component analysis and Daugman algorithm with ORL, YALE, CASIA and Real face dataset to combine face and iris recognition to improve the recognition efficiency.

Principal component analysis daugman algorithm face recognition iris recognition person identification.

Cited by 7

A Hybrid Approach to Multimodal Biometric Recognition Based on Feature-level Fusion of Face, Two Irises, and Both Thumbprints

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A Hybrid Approach for Multimodal Biometric Recognition based on Feature Level Fusion in Reproducing Kernel Hilbert Space

Mohammad H. Safavipour, Mohammad A. Doostari, Hamed Sadjedi · 2022 30th International Conference on Electrical Engineering (ICEE) · 2022

Deep Hybrid Multimodal Biometric Recognition System Based on Features‐Level Deep Fusion of Five Biometric Traits

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IRIS RECOGNITION USING SUPERVISED REGULARIZED MULTIDIMENSIONAL SCALING

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