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A new method for the synthesis of signature data with natural viability

A new method for the synthesis of signature data with natural viability
A new method for the synthesis of signature data with natural viability
The collection of human biometric test data for system development and evaluation within any chosen modality generally requires significant time and effort if data are to be obtained in workable quantities. To overcome this problem, techniques to generate synthetic data have been developed. This paper describes a novel technique for the automatic synthesis of human handwritten-signature images, which introduces modeled variability within the generated output based on positional variation that is naturally found within genuine source data. The synthesized data were found to generate similar verification rates to those obtained using genuine data with the use of a commercial verification engine, thereby indicating the suitability of the data synthesized by using this method for a wide range of application scenarios.
691-699
Rbasse, Cedric
2c07b4a6-5e31-4387-9896-0e98a77d2b88
Guest, Richard M.
93533dbd-b101-491b-83cc-39ccfdc18165
Fairhurst, Michael C.
6a82d154-93fe-4657-bcee-934d5c888192
Rbasse, Cedric
2c07b4a6-5e31-4387-9896-0e98a77d2b88
Guest, Richard M.
93533dbd-b101-491b-83cc-39ccfdc18165
Fairhurst, Michael C.
6a82d154-93fe-4657-bcee-934d5c888192

Rbasse, Cedric, Guest, Richard M. and Fairhurst, Michael C. (2008) A new method for the synthesis of signature data with natural viability. IEEE Transactions on Systems, Man and Cybernetics, Part B: Cybernetics, 38 (3), 691-699. (doi:10.1109/TSMCB.2008.918575).

Record type: Article

Abstract

The collection of human biometric test data for system development and evaluation within any chosen modality generally requires significant time and effort if data are to be obtained in workable quantities. To overcome this problem, techniques to generate synthetic data have been developed. This paper describes a novel technique for the automatic synthesis of human handwritten-signature images, which introduces modeled variability within the generated output based on positional variation that is naturally found within genuine source data. The synthesized data were found to generate similar verification rates to those obtained using genuine data with the use of a commercial verification engine, thereby indicating the suitability of the data synthesized by using this method for a wide range of application scenarios.

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Published date: 25 April 2008

Identifiers

Local EPrints ID: 489487
URI: http://eprints.soton.ac.uk/id/eprint/489487
PURE UUID: dc82dd8c-3d58-467c-8cc5-9364808beda2
ORCID for Richard M. Guest: ORCID iD orcid.org/0000-0001-7535-7336

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Date deposited: 25 Apr 2024 16:32
Last modified: 28 Apr 2024 02:05

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Contributors

Author: Cedric Rbasse
Author: Richard M. Guest ORCID iD
Author: Michael C. Fairhurst

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