Summary
In this work, a multibiometric system has been developed to overcome the drawbacks associated with monomodal biometric systems, such as noise, intra-class variability, distinctiveness, non-universality and spoof attacks. Information from three different Fisher’s Linear Discriminant driven monomodal experts based on face, ear and signature biometric traits are combined through decision level fusion method. AND/OR, majority voting, weighted majority voting and behavioural knowledge space approaches of decision level fusion method are examined to achieve a higher recognition accuracy. Experimental results indicate that fusing information from multiple biometric traits can results in higher recognition rates. The system can be a contribution to homeland security or other intelligence departments.
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Monwar, M.M., Gavrilova, M. (2008). A Robust Authentication System Using Multiple Biometrics. In: Lee, R., Kim, HK. (eds) Computer and Information Science. Studies in Computational Intelligence, vol 131. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-79187-4_17
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DOI: https://doi.org/10.1007/978-3-540-79187-4_17
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