Ensemble-based methods for cancellable biometrics

Authors:
Anne Canuto;Michael Fairhurst;Laura E. A. Santana;Fernando Pintro;Antonino Feitosa Neto
Affiliations:
Dep of Informatics and Applied Mathematics Federal University of RN, Natal Brazil and School of Engineering and Digital Arts University of Kent, Canterbury, UK;School of Engineering and Digital Arts University of Kent, Canterbury, UK;Dep of Informatics and Applied Mathematics Federal University of RN, Natal Brazil;Dep of Informatics and Applied Mathematics Federal University of RN, Natal Brazil;Dep of Informatics and Applied Mathematics Federal University of RN, Natal Brazil
Venue:
ICANN'10 Proceedings of the 20th international conference on Artificial neural networks: Part I
Year:
2010

Citing 6
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Abstract

In this paper, we investigate the use of genetic algorithms and ensemble systems in cancellable biometrics, using fingerprint-based identification to illustrate the possible benefits accruing. The main aim is to analyze the performance of these well-established structures on transformed biometric data to determine whether they have a positive effect on the performance of this complex and difficult task.