Abstract
This paper proposes to combine the fingerprint and handgeometry verification decisions using a reduced multivariate polynomials model. Main advantage of this method over those neural network based methods is that only a single step is required for training and the training is optimal. Numerical experiments using a database containing over 100 identities show significant improvement of Receiver Operating Characteristics as compared to that of individual biometrics. Moreover, the result outperforms a few commonly used methods using the same database.
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Toh, KA., Xiong, W., Yau, WY., Jiang, X. (2003). Combining Fingerprint and Hand-Geometry Verification Decisions. In: Kittler, J., Nixon, M.S. (eds) Audio- and Video-Based Biometric Person Authentication. AVBPA 2003. Lecture Notes in Computer Science, vol 2688. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44887-X_80
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DOI: https://doi.org/10.1007/3-540-44887-X_80
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