Combining Multiple Biometric Traits Using Asymmetric Aggregation Operators for Improved Person Recognition

Author:

Herbadji AbderrahmaneORCID,Akhtar ZahidORCID,Siddique KamranORCID,Guermat Noubeil,Ziet Lahcene,Cheniti Mohamed,Muhammad KhanORCID

Abstract

Biometrics is a scientific technology to recognize a person using their physical, behavior or chemical attributes. Biometrics is nowadays widely being used in several daily applications ranging from smart device user authentication to border crossing. A system that uses a single source of biometric information (e.g., single fingerprint) to recognize people is known as unimodal or unibiometrics system. Whereas, the system that consolidates data from multiple biometric sources of information (e.g., face and fingerprint) is called multimodal or multibiometrics system. Multibiometrics systems can alleviate the error rates and some inherent weaknesses of unibiometrics systems. Therefore, we present, in this study, a novel score level fusion-based scheme for multibiometric user recognition system. The proposed framework is hinged on Asymmetric Aggregation Operators (Asym-AOs). In particular, Asym-AOs are estimated via the generator functions of triangular norms (t-norms). The extensive set of experiments using seven publicly available benchmark databases, namely, National Institute of Standards and Technology (NIST)-Face, NIST-Multimodal, IIT Delhi Palmprint V1, IIT Delhi Ear, Hong Kong PolyU Contactless Hand Dorsal Images, Mobile Biometry (MOBIO) face, and Visible light mobile Ocular Biometric (VISOB) iPhone Day Light Ocular Mobile databases have been reported to show efficacy of the proposed scheme. The experimental results demonstrate that Asym-AOs based score fusion schemes not only are able to increase authentication rates compared to existing score level fusion methods (e.g., min, max, t-norms, symmetric-sum) but also is computationally fast.

Publisher

MDPI AG

Subject

Physics and Astronomy (miscellaneous),General Mathematics,Chemistry (miscellaneous),Computer Science (miscellaneous)

Reference28 articles.

Cited by 11 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Multi-modal Authentication Model for Occluded Faces in a Challenging Environment;IEEE Transactions on Emerging Topics in Computational Intelligence;2024

2. An Approach for Full Reinforcement-Based Biometric Score Fusion;IEEE Access;2024

3. Deep neural networks based contactless fingerprint recognition;2022 2nd International Conference on New Technologies of Information and Communication (NTIC);2022-12-21

4. A fuzzy connective score fusion technique for 2D and 3D palmprint authentication system;Evolving Systems;2022-12-18

5. The Submodular Inequality of Aggregation Operators;Symmetry;2022-11-08

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