Analysis of handwritten personal signatures for identity verification
It is becoming increasingly necessary to be able to verify personnel identities quickly and accurately. The design of automated methods of performing this task is therefore of prime concern. Basing such an automated identity verifier on a generally accepted means of identity authentication such as t...
Main Author: | |
---|---|
Language: | English |
Published: |
2010
|
Online Access: | http://hdl.handle.net/2429/22792 |
id |
ndltd-UBC-oai-circle.library.ubc.ca-2429-22792 |
---|---|
record_format |
oai_dc |
spelling |
ndltd-UBC-oai-circle.library.ubc.ca-2429-227922018-01-05T17:41:48Z Analysis of handwritten personal signatures for identity verification Omoruto, Francis Emmanuel Emauke It is becoming increasingly necessary to be able to verify personnel identities quickly and accurately. The design of automated methods of performing this task is therefore of prime concern. Basing such an automated identity verifier on a generally accepted means of identity authentication such as the handwritten personal signature would make it quite widely acceptable in the community. Previous work in automated identity authentication by signature verification has shown that it is feasible to achieve a degree of accuracy quite superior to the average performance of human verifiers in a similar environment. In this thesis, the implementation of basic tools for the acquisition and analysis of certain signature variables for identity verification is reported. The larger set of possible metrics for a signature are described together with some of the criteria for the selection of the subset examined. The results of a pilot study utilizing these tools indicate the potential for a viable commercial application of the technique. Applied Science, Faculty of Electrical and Computer Engineering, Department of Graduate 2010-03-26T23:44:25Z 2010-03-26T23:44:25Z 1980 Text Thesis/Dissertation http://hdl.handle.net/2429/22792 eng For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use. |
collection |
NDLTD |
language |
English |
sources |
NDLTD |
description |
It is becoming increasingly necessary to be able to verify personnel identities quickly and accurately. The design of automated methods of performing this task is therefore of prime concern. Basing such an automated identity verifier on a generally accepted means of identity authentication such as the handwritten personal signature would make it quite widely acceptable in the community.
Previous work in automated identity authentication by signature verification has shown that it is feasible to achieve a degree of accuracy quite superior to the average performance of human verifiers in a similar environment. In this thesis, the implementation of basic tools for the acquisition and analysis of certain signature variables for identity verification is reported. The larger set of possible metrics for a signature are described together with some of the criteria for the selection of the subset examined.
The results of a pilot study utilizing these tools indicate the potential for a viable commercial application of the technique. === Applied Science, Faculty of === Electrical and Computer Engineering, Department of === Graduate |
author |
Omoruto, Francis Emmanuel Emauke |
spellingShingle |
Omoruto, Francis Emmanuel Emauke Analysis of handwritten personal signatures for identity verification |
author_facet |
Omoruto, Francis Emmanuel Emauke |
author_sort |
Omoruto, Francis Emmanuel Emauke |
title |
Analysis of handwritten personal signatures for identity verification |
title_short |
Analysis of handwritten personal signatures for identity verification |
title_full |
Analysis of handwritten personal signatures for identity verification |
title_fullStr |
Analysis of handwritten personal signatures for identity verification |
title_full_unstemmed |
Analysis of handwritten personal signatures for identity verification |
title_sort |
analysis of handwritten personal signatures for identity verification |
publishDate |
2010 |
url |
http://hdl.handle.net/2429/22792 |
work_keys_str_mv |
AT omorutofrancisemmanuelemauke analysisofhandwrittenpersonalsignaturesforidentityverification |
_version_ |
1718592124924985344 |