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 16-abr-2024