NDLI: Score-level fusion using generalized extreme value distribution and DSmT, for multi-biometric systems

Content Provider	IET Digital Library
Author	Sharma, Renu Das, Sukhendu Joshi, Padmaja
Abstract	Human recognition in a multi-biometric system is performed by combining biometric clues from different sources (multiple sensors, units, algorithms, samples and modalities) at different levels (sensor, feature, score, rank and decision level). Low computational complexity and adequate data for fusion make the score-level fusion a preferable option over other levels of fusion. However, incompatibility issue prevails at this level as scores obtained from different uni-biometric systems are disparate in nature. This disparity can be resolved by using score normalisation before fusion. This study first analysed the effect of generalised extreme value distribution-based score normalisation technique on different fusion techniques and then proposes an efficient score fusion technique based on Dezert–Smarandache theory (DSmT). A unique blend of belief assignment and decision-making methods in the DSmT framework is proposed for score-level fusion. For evaluation of the proposed method, experiments are performed on multi-algorithm, multi-unit and multi-modal biometrics systems created from three publicly available datasets: (i) NIST BSSR1 multi-biometric score database, (ii) face recognition grand challenge (FRGC) V2.0 and (iii) LG4000 iris dataset. Comparative studies of performance analysis show the efficiency of the authors’ proposed method over other recently published state-of-the-art fusion methods.
Starting Page	474
Ending Page	481
Page Count	8
ISSN	20474938
Volume Number	7
e-ISSN	20474946
Issue Number	Issue 5, Sep (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-bmt/7/5
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-bmt.2017.0076
Journal	IET Biometrics
Publisher Date	2018-02-12
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Biometric Clues Biomimetics Computational Complexity Computer Vision And Image Processing Technique Data Security Dezert-Smarandache Theory DSmT Extreme Value Distribution-based Score Normalisation Technique Face Recognition Face Recognition Grand Challenge FRGC Generalised Extreme Value Distribution Human Recognition Image Recognition Iris Recognition LG4000 Iris Dataset Multibiometric System NIST BSSR1 Multi-biometric Score Database Score-level Fusion Sensor Fusion Uni-biometric System
Content Type	Text
Resource Type	Article
Subject	Signal Processing Computer Vision and Pattern Recognition Software

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