RT info:eu-repo/semantics/bookPart T1 Automatic online signature verification using HMMs with user-dependent structure A1 Pascual Gaspar, Juan Manuel A1 Cardeñoso Payo, Valentín K1 Online signature verification K1 Verificación de firma electrónica K1 Hidden Markov models K1 Modelos ocultos de Markov K1 2405 Biometría AB A novel strategy for Automatic online Signature Verification based on hidden Markov models (HMM) with user-dependent structure is presented in this work. Under this approach, the number of states and Gaussians giving the optimal prediction results are independently selected for each user. With this simple strategy just three genuine signatures could be used for training, with an EER under 2.5% obtained for the basic set of raw signature parameters provided by the acquisition device. This results increment by a factor of six the accuracy obtained with the typical approach in which claim-independent structure is used for the HMMs. PB Springer SN 978-3-540-74549-5 YR 2007 FD 2007 LK http://uvadoc.uva.es/handle/10324/41029 UL http://uvadoc.uva.es/handle/10324/41029 LA eng NO Lee, S.W.; Li, S.Z. (eds.). Advances in Biometrics: Second International Conference of Biometrics 2007. Berlin: Springer, 2007, p. 1057-1066 NO Producción Científica DS UVaDOC RD 22-dic-2024