Thesis (MSc)--University of Stellenbosch, 2002. / ENGLISH ABSTRACT: The science of signature verification is concerned with identifying individuals by their handwritten
signatures. It is assumed that the signature as such is a unique feature amongst
individuals and the creation thereof requires a substantial amount of hidden information
which makes it difficult for another individual to reproduce the signature. Modern technology
has produced devices which are able to capture information about the signing process
beyond what is visible to the naked eye. A dynamic signature verification system is concerned
with utilizing not only visible, i.e. shape related information but also invisible, hidden dynamical
characteristics of signatures. These signature characteristics need to be subjected to
analysis and modelling in order to automate use of signatures as an identification metric. We
investigate the applicability of hidden Markov models to the problem of modelling signature
characteristics and test their ability to distinguish between authentic signatures and forgeries. / AFRIKAANSE OPSOMMING: Die wetenskap van handtekeningverifikasie is gemoeid met die identifisering van individue
deur gebruik te maak van hulle persoonlike handtekening. Dit berus op die aanname dat 'n
handtekening as sulks uniek is tot elke individu en die generering daarvan 'n genoeg mate van
verskuilde inligting bevat om die duplisering daarvan moeilik te maak vir 'n ander individu.
Moderne tegnologie het toestelle tevoorskyn gebring wat die opname van eienskappe van
die handtekeningproses buite die bestek van visuele waarneming moontlik maak. Dinamiese
handtekeningverifikasie is gemoeid met die gebruik nie alleen van die sigbare manefestering
van 'n handtekening nie, maar ook van die verskuilde dinamiese inligting daarvan om dit sodoende
'n lewensvatbare tegniek vir die identifikasie van individue te maak. Hierdie sigbare en
onsigbare eienskappe moet aan analise en modellering onderwerp word in die proses van outomatisering
van persoonidentifikasie deur handtekeninge. Ons ondersoek die toepasbaarheid
van verskuilde Markov-modelle tot die modelleringsprobleem van handtekeningkarakteristieke
en toets die vermoë daarvan om te onderskei tussen egte en vervalste handtekeninge.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:sun/oai:scholar.sun.ac.za:10019.1/52876 |
| Date | 12 1900 |
| Creators | Wessels, Tiaan |
| Contributors | Omlin, C.W., Stellenbosch University. Faculty of Science. Dept. of Mathematical Sciences (applied, computer, mathematics). |
| Publisher | Stellenbosch : Stellenbosch University |
| Source Sets | South African National ETD Portal |
| Language | en_ZA |
| Detected Language | Unknown |
| Type | Thesis |
| Format | 145 p. : ill. |
| Rights | Stellenbosch University |
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