A new approach to automatic signature complexity assessment
A new approach to automatic signature complexity assessment
Understanding signature complexity has been shown to be a crucial facet for both forensic and biometric appbcations. The signature complexity can be defined as the difficulty that forgers have when imitating the dynamics (constructional aspects) of other users signatures. Knowledge of complexity along with others facets such stability and signature length can lead to more robust and secure automatic signature verification systems. The work presented in this paper investigates the creation of a novel mathematical model for the automatic assessment of the signature complexity, analysing a wider set of dynamic signature features and also incorporating a new layer of detail, investigating the complexity of individual signature strokes. To demonstrate the effectiveness of the model this work will attempt to reproduce the signature complexity assessment made by experienced FDEs on a dataset of 150 signature samples.
Miguel-Hurtado, Oscar
57a8ef90-e39d-4731-a271-0399d7201d34
Guest, Richard
93533dbd-b101-491b-83cc-39ccfdc18165
Chatzisterkotis, Thomas
ae95ca59-1b9e-43c9-815b-9d905996e423
Miguel-Hurtado, Oscar
57a8ef90-e39d-4731-a271-0399d7201d34
Guest, Richard
93533dbd-b101-491b-83cc-39ccfdc18165
Chatzisterkotis, Thomas
ae95ca59-1b9e-43c9-815b-9d905996e423
Miguel-Hurtado, Oscar, Guest, Richard and Chatzisterkotis, Thomas
(2017)
A new approach to automatic signature complexity assessment.
In 2016 IEEE International Carnahan Conference on Security Technology (ICCST).
IEEE.
7 pp
.
(doi:10.1109/CCST.2016.7815678).
Record type:
Conference or Workshop Item
(Paper)
Abstract
Understanding signature complexity has been shown to be a crucial facet for both forensic and biometric appbcations. The signature complexity can be defined as the difficulty that forgers have when imitating the dynamics (constructional aspects) of other users signatures. Knowledge of complexity along with others facets such stability and signature length can lead to more robust and secure automatic signature verification systems. The work presented in this paper investigates the creation of a novel mathematical model for the automatic assessment of the signature complexity, analysing a wider set of dynamic signature features and also incorporating a new layer of detail, investigating the complexity of individual signature strokes. To demonstrate the effectiveness of the model this work will attempt to reproduce the signature complexity assessment made by experienced FDEs on a dataset of 150 signature samples.
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e-pub ahead of print date: 16 January 2017
Venue - Dates:
2016 IEEE International Carnahan Conference on Security Technology, , Orlando, United States, 2016-10-24 - 2016-10-27
Identifiers
Local EPrints ID: 489710
URI: http://eprints.soton.ac.uk/id/eprint/489710
PURE UUID: bbbefe6d-fafc-4377-b6c8-6cb860d2d070
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Date deposited: 30 Apr 2024 17:00
Last modified: 01 May 2024 02:10
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Contributors
Author:
Oscar Miguel-Hurtado
Author:
Richard Guest
Author:
Thomas Chatzisterkotis
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