Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/19113
Title: Synthetic signature generation for automatic signature verification
Other Titles: Generación de firmas sintéticas para verificación automática de firmas
Authors: Díaz Cabrera, Moisés 
Director: Ferrer Ballester, Miguel Ángel 
Morales Moreno, Aythami
UNESCO Clasification: 33 Ciencias tecnológicas
3304 Tecnología de los ordenadores
Issue Date: 2016
Abstract: As a bridge between synthesis of biometric data and human modeling, innovative methods are addressed in this dissertation to generate synthetic handwriting signatures following the insights learnt from the motor equivalence theory. As such, in this Thesis several procedures are proposed to generate i) fully synthetic signature databases and ii) duplicated signatures from a single real specimen. The goal of the proposed methods is to verify whether the generated signatures are able to introduce realistic intra and inter-personal variability in signature-based biometric systems as well as to certify their human-like appearance. For these purposes, machine-oriented and human-oriented evaluations are discussed in the frameworks used in this document.
Learning to write is complex and usually starts with lines and scribbles. Before reaching a mature handwriting, children start to know the letters’ shapes and their sequence, although the children’s motor control is not yet accurate. Modeling this behavior in a mathematically way would allow to understand the mechanical processes from the initial thought of signing to its complete fulfillment.
Description: Mención Internacional
URI: http://hdl.handle.net/10553/19113
Rights: by-nc-nd
Appears in Collections:Tesis doctoral
Thumbnail
thesis
Adobe PDF (4,03 MB)
Thumbnail
Adobe PDF (12,27 MB)
Show full item record

Page view(s)

20
checked on Feb 27, 2021

Download(s)

149
checked on Feb 27, 2021

Google ScholarTM

Check


Share



Export metadata



This item is licensed under a Creative Commons License Creative Commons