This paper presents a personal verification system based on two different biometric traits: handwritten signature and speech. The signature verification system uses contour-based features and a Dynamic Time Warping technique for matching. The speaker verification system uses cepstral based coefficients and is based on a Hidden Markov Model statistical classifier. In the decision combination stage, the decisions provided by the two systems are combined according to a simple abstract-level combination approach. The experimental results related to a real-scenario demonstrate the effectiveness of the proposed approach and highlight some profitable directions for further developments. © 2008 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Impedovo, D., Pirlo, G., & Refice, M. (2008). Handwritten signature and speech: Preliminary experiments on multiple source and classifiers for personal identity verification. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5158 LNCS, pp. 181–191). https://doi.org/10.1007/978-3-540-85303-9_17
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