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dc.contributor.advisorPatidar, Kailash C.
dc.contributor.authorMalladi, Raghuram
dc.date.accessioned2014-09-02T07:52:27Z
dc.date.available2014-09-02T07:52:27Z
dc.date.issued2013
dc.identifier.urihttp://hdl.handle.net/11394/3617
dc.descriptionPhilosophiae Doctor - PhDen_US
dc.description.abstractIn this thesis, we explore dynamic signature verification systems. Unlike other signature models, we use genuine signatures in this project as they are more appropriate in real world applications. Signature verification systems are typical examples of biometric devices that use physical and behavioral characteristics to verify that a person really is who he or she claims to be. Other popular biometric examples include fingerprint scanners and hand geometry devices. Hand written signatures have been used for some time to endorse financial transactions and legal contracts although little or no verification of signatures is done. This sets it apart from the other biometrics as it is well accepted method of authentication. Until more recently, only hidden Markov models were used for model construction. Ongoing research on signature verification has revealed that more accurate results can be achieved by combining results of multiple models. We also proposed to use combinations of multiple single variate models instead of single multi variate models which are currently being adapted by many systems. Apart from these, the proposed system is an attractive way for making financial transactions more secure and authenticate electronic documents as it can be easily integrated into existing transaction procedures and electronic communicationsen_US
dc.language.isoenen_US
dc.subjectSignature verification systemen_US
dc.subjectHand written signaturesen_US
dc.subjectDynamic signature verificationen_US
dc.subjectHidden Markov Modelsen_US
dc.subjectMultiple single variate modelsen_US
dc.subjectFeature extractionen_US
dc.subjectBiometricsen_US
dc.subjectTime series modellingen_US
dc.titleAutomatic signature verification systemen_US
dc.rights.holderuwcen_US


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