We provide an introduction to Multiple Classifier Systems (MCS) including basic
nomenclature and describing key elements: classifier dependencies, type of classifier …

The present paper is Part 2 in this series of two papers. In Part 1 we provided an introduction
to Multiple Classifier Systems (MCS) with a focus into the fundamentals: basic nomenclature …

This paper proposes a unified framework for quality-based fusion of multimodal biometrics.
Quality-dependent fusion algorithms aim to dynamically combine several classifier …

A multimodal biometric system integrates information from multiple biometric sources to
compensate for the limitations in performance of each individual biometric system. We …

ABSTRACT A biometric system is essentially a pattern recognition system that operates by
acquiring biometric data from an individual, extracting a feature set from the acquired data …

The interest on biometric recognition systems for person authentication has experienced an
important growth in the last decade. One of the key factors of this success is the availability …

Unimodal biometric systems have to contend with a variety of problems such as noisy data,
intra-class variations, restricted degrees of freedom, non-universality, spoof attacks, and …

It has been demonstrated in the literature that the combining of different biometric traits is a
powerful tool to overcome the limitations imposed by a single biometric system. The fusion of …

Biometrics refers to the automatic recognition of individuals based on their physiological
and/or behavioral characteristics. Unimodal biometric systems perform person recognition …

The concept of multimodal biometrics is gaining importance to realise reliable, accurate and
robust authentication systems. In multimodal biometrics, information fusion can be done at …