An Evaluation of Score Level Fusion Approaches for Fingerprint and Finger-vein Biometrics

  • Kamer Vishi
  • Vasileios Mavroeidis

Abstract

Biometric systems have to address many requirements, such as large population
coverage, demographic diversity, varied deployment environment, as
well as practical aspects like performance and spoofing attacks. Traditional
unimodal biometric systems do not fully meet the aforementioned requirements
making them vulnerable and susceptible to different types of attacks.
In response to that, modern biometric systems combine multiple biometric
modalities at different fusion levels. The fused score is decisive to classify
an unknown user as a genuine or impostor. In this paper, we evaluate combinations
of score normalization and fusion techniques using two modalities
(fingerprint and finger-vein) with the goal of identifying which one achieves
better improvement rate over traditional unimodal biometric systems. The
individual scores obtained from finger-veins and fingerprints are combined
at score level using three score normalization techniques (min-max, z-score,
hyperbolic tangent) and four score fusion approaches (minimum score, maximum
score, simple sum, user weighting). The experimental results proved
that the combination of hyperbolic tangent score normalization technique
with the simple sum fusion approach achieve the best improvement rate of
99.98%.
Keywords: multibiometrics, biometric fusion, fingerprint, finger-vein,
authentication systems, identity management, privacy, security

Published
2018-01-23
Section
Norsk Informasjonssikkerhetskonferanse 2017