Abstract
In this paper, we present an automated multimodal biometric system for the detection and recognition of humans using face and ear as input. The system is totally automated, with a trained detection system for face and for ear. We look at individual recognition rates for both face and ear, and then at combined recognition rates, and show that an automated multimodal biometric system achieves significant performance gains. We also discuss methods of combining biometric input and the recognition rates that each achieves.
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Luciano, L., Krzyżak, A. (2009). Automated Multimodal Biometrics Using Face and Ear. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2009. Lecture Notes in Computer Science, vol 5627. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02611-9_45
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DOI: https://doi.org/10.1007/978-3-642-02611-9_45
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-02610-2
Online ISBN: 978-3-642-02611-9
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