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oai:uvadoc.uva.es:10324/410292021-06-24T07:19:58Zcom_10324_27504com_10324_954com_10324_894col_10324_27506

Pascual Gaspar, Juan Manuel Cardeñoso Payo, Valentín 2020-06-11T12:01:17Z 2020-06-11T12:01:17Z 2007 Lee, S.W.; Li, S.Z. (eds.). Advances in Biometrics: Second International Conference of Biometrics 2007. Berlin: Springer, 2007, p. 1057-1066 978-3-540-74549-5 http://uvadoc.uva.es/handle/10324/41029 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. eng info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-nd/3.0/ © 2007 Springer Attribution-NonCommercial-NoDerivs 3.0 Unported Automatic online signature verification using HMMs with user-dependent structure info:eu-repo/semantics/bookPart