On enhancing serial fusion based multi-biometric verification system

Resource type
Authors/contributors
Title
On enhancing serial fusion based multi-biometric verification system
Abstract
Design of a serial fusion based multi-biometric verification system requires fixing several parameters, such as reject thresholds at each stage of the architecture and the order in which each individual verifier is placed within the multi-stage system. Selecting the order of verifier is a crucial parameter to fix because of its high impact on verification errors. A wrong choice of verifier order might lead to tremendous user inconvenience by denying a large number of genuine users and might cause severe security breach by accepting impostors frequently. Unfortunately, this design issue has been poorly investigated in multi-biometric literature. In this paper, we address this design issue by performing experiments using three different serial fusion based multi-biometric verification schemes. We did our experiments on publicly available NIST multi-modal dataset. We tested 24 orders—all possible orders originated from four individual verifiers—on a four-stage biometric verification system. Our experimental results show that the verifier order “best-to-worst”, where the best performing individual verifier is placed in the first stage, the next best performing individual verifier is placed in the second stage, and so on, is the top performing order. In addition, we have proposed a modification to the traditional architecture of serial fusion based multi-biometric verification systems. With rigorous experiments on the NIST multi-modal dataset and using three serial fusion based multi-biometric verification schemes, we demonstrated that our proposed architecture significantly improves the performance of serial fusion based multi-biometric verification systems.
Publication
Applied Intelligence
Date
12/2018
Volume
48
Issue
12
Pages
4824-4833
Journal Abbr
Appl Intell
Citation Key
hossainEnhancingSerialFusion2018
Accessed
10/7/19, 11:15 PM
ISSN
0924-669X, 1573-7497
Language
English
Library Catalog
DOI.org (Crossref)
Extra
9 citations (Crossref) [2023-10-31] Citation Key Alias: hossainEnhancingSerialFusion2018a, lens.org/017-508-366-099-573, pop00310 tex.type: [object Object]
Citation
Hossain, M., Chen, J., & Rahman, K. (2018). On enhancing serial fusion based multi-biometric verification system. Applied Intelligence, 48(12), 4824–4833. https://doi.org/10.1007/s10489-018-1257-4