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CIARP
2003
Springer

Online Handwritten Signature Verification Using Hidden Markov Models

9 years 9 months ago
Online Handwritten Signature Verification Using Hidden Markov Models
Most people are used to signing documents and because of this, it is a trusted and natural method for user identity verification, reducing the cost of password maintenance and decreasing the risk of eBusiness fraud. In the proposed system, identity is securely verified and an authentic electronic signature is created using biometric dynamic signature verification. Shape, speed, stroke order, off-tablet motion, pen pressure and timing information are captured and analyzed during the real-time act of signing the handwritten signature. The captured values are unique to an individual and virtually impossible to duplicate. This paper presents a research of various HMM based techniques for signature verification. Different topologies are compared in order to obtain an optimized high performance signature verification system and signal normalization preprocessing makes the system robust with respect to writer variability.
Juan J. Igarza, Iñaki Goirizelaia, Koldo Es
Added 06 Jul 2010
Updated 06 Jul 2010
Type Conference
Year 2003
Where CIARP
Authors Juan J. Igarza, Iñaki Goirizelaia, Koldo Espinosa, Inma Hernáez, R. Méndez, J. Sánchez
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