We propose in this work to perform on-line signature verification by the fusion of two complementary verification modules. The first one considers a signature as a sequence of points and models the genuine signatures of a given signer by a Hidden Markov Model (HMM). Forgeries are used to compute a decision threshold. In the second module, global parameters of a signature are the inputs of a two-classes neural network trained for each signer on both the genuine and "other" signatures (genuine signatures of other signers). Fusion of the scores given by these two experts through a Support Vector Machine (SVM), allows improving the results over those of each module, on Philips' Database.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    On line signature verification: Fusion of a Hidden Markov Model and a neural network via a support vector machine


    Beteiligte:
    Fuentes, M. (Autor:in) / Garcia-Salicetti, S. (Autor:in) / Dorizzi, B. (Autor:in)


    Erscheinungsdatum :

    01.01.2002


    Format / Umfang :

    335508 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    On-Line Signature Verification: Fusion of a Hidden Markov Model and a Neural Network via a Support Vector Machine

    Fuentes, M. / Garcia-Salicetti, S. / Dorizzi, B. | British Library Conference Proceedings | 2002


    An On-Line Signature Verification System Using Hidden Markov Model in Polar Space

    Yoon, H. S. / Lee, J. Y. / Yang, H. S. | British Library Conference Proceedings | 2002



    A New On-Line Signature Verification Algorithm Using Variable Length Segmentation and Hidden Markov Models

    Shafiei, M. / Rabiee, H. / Institute of Electrical and Electronics Engineers | British Library Conference Proceedings | 2003