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Sensors 2012, 12(4), 4324-4338; doi:10.3390/s120404324

Integrating Iris and Signature Traits for Personal Authentication Using User-SpecificWeighting

1,*  and 2
1 School of Computer Science, University of KwaZulu-Natal, Westville Campus, Durban 4000, South Africa 2 School of Electrical, Electronic and Computer Engineering, Howard College, University of KwaZulu-Natal, Durban 4000, South Africa
* Author to whom correspondence should be addressed.
Received: 7 March 2012 / Revised: 22 March 2012 / Accepted: 22 March 2012 / Published: 29 March 2012
(This article belongs to the Special Issue Biomimetic Sensors, Actuators and Integrated Systems)
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Biometric systems based on uni-modal traits are characterized by noisy sensor data, restricted degrees of freedom, non-universality and are susceptible to spoof attacks. Multi-modal biometric systems seek to alleviate some of these drawbacks by providing multiple evidences of the same identity. In this paper, a user-score-based weighting technique for integrating the iris and signature traits is presented. This user-specific weighting technique has proved to be an efficient and effective fusion scheme which increases the authentication accuracy rate of multi-modal biometric systems. The weights are used to indicate the importance of matching scores output by each biometrics trait. The experimental results show that our biometric system based on the integration of iris and signature traits achieve a false rejection rate (FRR) of 0.08% and a false acceptance rate (FAR) of 0.01%.
Keywords: biometrics fusion; multi-modal biometrics; iris; signature; user-specific weighting biometrics fusion; multi-modal biometrics; iris; signature; user-specific weighting
This is an open access article distributed under the Creative Commons Attribution License (CC BY) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Viriri, S.; Tapamo, J.R. Integrating Iris and Signature Traits for Personal Authentication Using User-SpecificWeighting. Sensors 2012, 12, 4324-4338.

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