Tools
Tools
Fairhurst, Michael C. and Kaplani, Eleni 
ORCID: https://orcid.org/0000-0002-4987-4388
(2002)
Strategies for exploiting signature verification based on complexity estimates.
In: UNSPECIFIED.
Abstract
Biometrics is a diverse and increasingly important field, covering many modalities and types of individual characteristics. The biometric modality with perhaps the longest history, and one which certainly enjoys the widest degree of public acceptance, is the handwritten signature [1]. However, checking and analysing handwritten signatures as a means of establishing or verifying identity is both a challenge for technology (i.e. algorithms for robust automatic signature verification are constantly sought) and for the powers of human perception, since there are many situations where signature checking by machine might be inappropriate or, at least at present, insufficiently reliable, for routine use. This is especially the case when the risk of forgery is high, or where acceptance of a nonauthentic signature could have serious consequences. Furthermore, it can reasonably be claimed that a better understanding of human ability in analysing and authenticating signatures can lead indirectly to the specification of more accurate and perhaps more robust techniques which can be implemented automatically. This paper will report on some important aspects of our work in the field of signature verification and, in particular, addresses some important issues relating to the human and machine identification of signature imitations/forgeries. We can envisage the handwritten signature playing a key role in two related broad scenarios. First, human checking (by direct visual inspection) is still a common means of determining/confirming identity or authorising transactions, and the pervasiveness of this type of activity should not be underestimated. Secondly, there is an increasing need for automated (machinebased) verification of the handwritten signature (e.g. in electronic sign-on systems, or where improved objectivity and accuracy, such as in point-of-sale applications, is at a premium). It is this continuing need for both human and machine-based signature verification which provides the focus for the work reported, addressing issues concerning the form and structure of the signature in relation to the reliability with which genuine and fraudulent samples may be distinguished.
| Item Type: | Conference or Workshop Item (Other) |
|---|---|
| Additional Information: | BMVA Symposium on Advancing Biometric Technologies, Royal Statistical Society, London, U.K. |
| Faculty \ School: | Faculty of Science > School of Mathematics (former - to 2024) |
| UEA Research Groups: | Faculty of Science > Research Groups > Sustainable Energy |
| Depositing User: | Pure Connector |
| Date Deposited: | 11 Nov 2015 11:00 |
| Last Modified: | 07 Nov 2024 12:31 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/55090 |
| DOI: |
Actions (login required)
 |
View Item |