Identificador persistente para citar o vincular este elemento:
http://hdl.handle.net/10553/118769
Campo DC | Valor | idioma |
---|---|---|
dc.contributor.advisor | Travieso González, Carlos Manuel | - |
dc.contributor.advisor | Bönninger, Ingrid | - |
dc.contributor.author | Kutzner, Tobias H. | - |
dc.date.accessioned | 2022-10-04T13:57:06Z | - |
dc.date.available | 2022-10-04T13:57:06Z | - |
dc.date.issued | 2017 | en_US |
dc.identifier.uri | http://hdl.handle.net/10553/118769 | - |
dc.description.abstract | The aim of the thesis is to investigate the enhanced safety of authentication systems through the use of handwritten secure password. In state of the art we find some online and a lot of offline text and signature verification and recognition systems, but no system that use a handwritten secure password for authentication. Therefor in this thesis it will be investigated to increase safety through the use of a handwritten secure password for authentication systems. The improvement of results in writer recognition by increasing the safety of handwritten password and exploring the possibilities of writer recognition of short texts, such as passwords under practical conditions shall be examined. For this purpose, both available public databases as well as own databases with handwritten datasets will be used / produced as research basis. As input device a device with a touch screen display (smart phone, tablet) shall be used. The preprocessing of the data, extracting the features and the classification is investigated and applied. Research for a suitable segmentation as a function of the data format will be examined. The usefulness of new features will be tested in the databases considering different standard machine learning –based methods for feature selection and/or classification. Not only theoretical investigation with popular data mining tools will be applied. The system will be tested in a real-world application using a prototype that will be developed on Java for handwriting password verification and writer identification. | en_US |
dc.language | eng | en_US |
dc.subject | 3307 Tecnología electrónica | en_US |
dc.title | Writer identification using online handwritten passwords | en_US |
dc.type | info:eu-repo/semantics/doctoralThesis | en_US |
dc.type | Thesis | en_US |
dc.type | Thesis | en_US |
dc.contributor.centro | Instituto Universitario de Ciencias y Tecnologías Cibernéticas | en_US |
dc.investigacion | Ingeniería y Arquitectura | en_US |
dc.type2 | Tesis doctoral | en_US |
dc.description.notas | Programa de doctorado: Cibernética y Telecomunicación | en_US |
dc.utils.revision | Sí | en_US |
dc.identifier.ulpgc | Sí | en_US |
dc.contributor.buulpgc | BU-TEL | en_US |
item.fulltext | Con texto completo | - |
item.grantfulltext | open | - |
crisitem.advisor.dept | GIR IDeTIC: División de Procesado Digital de Señales | - |
crisitem.advisor.dept | IU para el Desarrollo Tecnológico y la Innovación | - |
crisitem.advisor.dept | Departamento de Señales y Comunicaciones | - |
Colección: | Tesis doctoral |
Visitas
53
actualizado el 09-mar-2024
Descargas
53
actualizado el 09-mar-2024
Google ScholarTM
Verifica
Comparte
Exporta metadatos
Los elementos en ULPGC accedaCRIS están protegidos por derechos de autor con todos los derechos reservados, a menos que se indique lo contrario.