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

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

1,* email and 2email
Received: 7 March 2012; in revised form: 22 March 2012 / Accepted: 22 March 2012 / Published: 29 March 2012
(This article belongs to the Special Issue Biomimetic Sensors, Actuators and Integrated Systems)
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract: 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
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MDPI and ACS Style

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

AMA Style

Viriri S, Tapamo JR. Integrating Iris and Signature Traits for Personal Authentication Using User-SpecificWeighting. Sensors. 2012; 12(4):4324-4338.

Chicago/Turabian Style

Viriri, Serestina; Tapamo, Jules R. 2012. "Integrating Iris and Signature Traits for Personal Authentication Using User-SpecificWeighting." Sensors 12, no. 4: 4324-4338.

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