Integrating Iris and Signature Traits for Personal Authentication Using User-Specific Weighting
نویسندگان
چکیده
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%.
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Survey of Different Biometrics Techniques Biometrics Systems Personal Authenticati on Medical Diagnosis Future Expectation Ethnology Exploration
Biometrics is the study of automatically recognizing humans by means of inherently unique physical or behavioural characteristics. The human physical characteristics like fingerprints, face, hand geometry, voice, Signature, palm and iris are known as biometrics. These features are used to provide an authentication for computer based security systems. The existing computer security systems used ...
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