Abstract
Face and signature based multimodal biometric systems are often required in various areas, such as banking biometric systems and secured mobile phone operating systems, among others. Our system combines these two biometric traits and provides better recognition performance compared with the systems based on a single biometric trait or modality. In multimodal biometric system, the most common fusion approach is integration at the matching score level because of the ease of combining and accessing the scores generated by different matchers. In this paper, we study the performance of a max-of-scores fusion technique based on the face and signature traits of a user. The experiments that were conducted on a database of 40 users indicate that the max-of-scores fusion-based method yields better authentication performance than single-face, single-signature, simple-sum or min-of-scores fusion-based biometric systems.
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Elmir, Y., Al-Maadeed, S., Amira, A., Hassaïne, A. (2012). A Multi-modal Face and Signature Biometric Authentication System Using a Max-of-Scores Based Fusion. In: Huang, T., Zeng, Z., Li, C., Leung, C.S. (eds) Neural Information Processing. ICONIP 2012. Lecture Notes in Computer Science, vol 7667. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34500-5_68
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DOI: https://doi.org/10.1007/978-3-642-34500-5_68
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