Mobile signature verification: feature robustness and performance comparison
Mobile signature verification: feature robustness and performance comparison
- Author(s): Marcos Martinez-Diaz ; Julian Fierrez ; Ram P. Krish ; Javier Galbally
- DOI: 10.1049/iet-bmt.2013.0081
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- Author(s): Marcos Martinez-Diaz 1 ; Julian Fierrez 1 ; Ram P. Krish 1 ; Javier Galbally 1
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View affiliations
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Affiliations:
1:
Biometric Recognition Group - ATVS, Escuela Politecnica Superior, Universidad Autonoma de Madrid, Campus de Cantoblanco, C/ Francisco Tomas y Valiente, 11, 28049 Madrid, Spain
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Affiliations:
1:
Biometric Recognition Group - ATVS, Escuela Politecnica Superior, Universidad Autonoma de Madrid, Campus de Cantoblanco, C/ Francisco Tomas y Valiente, 11, 28049 Madrid, Spain
- Source:
Volume 3, Issue 4,
December 2014,
p.
267 – 277
DOI: 10.1049/iet-bmt.2013.0081 , Print ISSN 2047-4938, Online ISSN 2047-4946
In this study, the effects of using handheld devices on the performance of automatic signature verification systems are studied. The authors compare the discriminative power of global and local signature features between mobile devices and pen tablets, which are the prevalent acquisition device in the research literature. Individual feature discriminant ratios and feature selection techniques are used for comparison. Experiments are conducted on standard signature benchmark databases (BioSecure database) and a state-of-the-art device (Samsung Galaxy Note). Results show a decrease in the feature discriminative power and a higher verification error rate on handheld devices. It is found that one of the main causes of performance degradation on handheld devices is the absence of pen-up trajectory information (i.e. data acquired when the pen tip is not in contact with the writing surface).
Inspec keywords: feature selection; mobile computing; handwriting recognition
Other keywords: feature selection techniques; performance comparison; handheld devices; automatic signature verification systems; feature robustness; global signature features; local signature features; mobile signature verification; pen-up trajectory information; prevalent acquisition device; standard signature benchmark databases
Subjects: Computer vision and image processing techniques; Image recognition; Ubiquitous and pervasive computing
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