Kaplani, Eleni (2003) Human and computer-based verification of handwritten signatures. Doctor of Philosophy (PhD) thesis, University of Kent. (doi:10.22024/UniKent/01.02.94454) (KAR id:94454)
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Language: English
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Official URL: https://doi.org/10.22024/UniKent/01.02.94454 |
Abstract
The work reported in this thesis is set within the broad field of biometrics and, especially, is concerned with the link between human and machine -based biometric processing. The use of the handwritten signature as a biometric for authenticating the identity of individuals is investigated and aspects of the handwritten signature known to influence its susceptibility to fraudulent penetration or a false rejection of its original are particularly assessed. Two approaches to handwritten signature verification are considered: through an automatic signature verification system and by means of human visual inspection. A strong emphasis is given in the processing of static signature information. Experimental studies on human perceptual judgements regarding the complexity of signatures and their intra-class variability directed the development and assessment of automatic algorithmic solutions that reflect human perceptual criteria. A novel method is developed to quantitatively estimate the degree of a signature’s complexity based on the static signature image alone. Valuable insight is gained, through a number of experiments on human visual inspection of handwritten signatures, into strategies employed by humans in analysing signatures and the key factors that affect human performance in correctly verifying signatures’ authenticity, allowing predictions about the likelihood of a signature’s susceptibility to forgery and proposing practical scenarios for improvement. Finally, the integration of knowledge gained from the investigation of the advanced human perceptual capabilities in inspecting handwritten signature samples with automatic signature verification processing is investigated and a number of possible schemes are proposed. The possibility of improvement is, thus, offered with respect to both automatic identity authentication and also regarding human related procedures in inspecting and authenticating handwritten signature samples, which remains an important aspect of signature checking in common use.
Item Type: | Thesis (Doctor of Philosophy (PhD)) |
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Thesis advisor: | Fairhurst, Michael |
DOI/Identification number: | 10.22024/UniKent/01.02.94454 |
Additional information: | This thesis has been digitised by EThOS, the British Library digitisation service, for purposes of preservation and dissemination. It was uploaded to KAR on 25 April 2022 in order to hold its content and record within University of Kent systems. It is available Open Access using a Creative Commons Attribution, Non-commercial, No Derivatives (https://creativecommons.org/licenses/by-nc-nd/4.0/) licence so that the thesis and its author, can benefit from opportunities for increased readership and citation. This was done in line with University of Kent policies (https://www.kent.ac.uk/is/strategy/docs/Kent%20Open%20Access%20policy.pdf). If you feel that your rights are compromised by open access to this thesis, or if you would like more information about its availability, please contact us at ResearchSupport@kent.ac.uk and we will seriously consider your claim under the terms of our Take-Down Policy (https://www.kent.ac.uk/is/regulations/library/kar-take-down-policy.html). |
Uncontrolled keywords: | biometrics, biometric processing, handwritten signatures |
Subjects: |
Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming, T Technology > T Technology (General) |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts |
SWORD Depositor: | SWORD Copy |
Depositing User: | SWORD Copy |
Date Deposited: | 09 May 2023 11:11 UTC |
Last Modified: | 09 May 2023 11:11 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/94454 (The current URI for this page, for reference purposes) |
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