Experimental results on fusion of multiple fingerprint matchers

Authors:
Gian Luca Marcialis;Fabio Roli
Affiliations:
Department of Electrical and Electronic Engineering, University of Cagliari, Cagliari, Italy;Department of Electrical and Electronic Engineering, University of Cagliari, Cagliari, Italy
Venue:
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
Year:
2003

Citing 7
Cited 3

On-Line Fingerprint Verification

IEEE Transactions on Pattern Analysis and Machine Intelligence
A Multichannel Approach to Fingerprint Classification

IEEE Transactions on Pattern Analysis and Machine Intelligence
Combining multiple matchers for a high security fingerprint verification system

Pattern Recognition Letters - Special issue on pattern recognition in practice VI
FVC2000: Fingerprint Verification Competition

IEEE Transactions on Pattern Analysis and Machine Intelligence
Neural Networks for Pattern Recognition

Neural Networks for Pattern Recognition
Proceedings of the Third International Workshop on Multiple Classifier Systems

MCS '02 Proceedings of the Third International Workshop on Multiple Classifier Systems
Filterbank-based fingerprint matching

IEEE Transactions on Image Processing

Fingerprint verification by fusion of optical and capacitive sensors

Pattern Recognition Letters
Fusion of multiple fingerprint matchers by single-layer perceptron with class-separation loss function

Pattern Recognition Letters - Special issue: Artificial neural networks in pattern recognition
Single-sensor multi-instance fingerprint and eigenfinger recognition using (weighted) score combination methods

International Journal of Biometrics

Quantified Score

Hi-index	0.00

Visualization

Abstract

Fingerprints are widely used in automatic identity verification systems. The core of such systems is the verification algorithm to match two fingerprints. So far, various method for fingerprint matching have been proposed, but few works investigated the fusion of two or more matching algorithms. In this paper, various methods for fusing such algorithms have been investigated. Experimental results showed that such fusion can outperform the best individual verification algorithm and increase the discrimination between genuine and impostor classes.