Journal
IEEE TRANSACTIONS ON CYBERNETICS
Volume 48, Issue 1, Pages 228-239Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCYB.2016.2630419
Keywords
Duplicated signatures; dynamic signature verification; kinematic theory of rapid human movements; single reference signature system (SRSS)
Categories
Funding
- Spanish Government's MCINN [TEC2016-77791-C4-1-R]
- European Union FEDER Program/Funds
- ULPGC
- Swiss National Science Foundation [P300P2-151279]
- NSERC CANADA [RGPIN-2015-06409]
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The dynamic signature is a biometric trait widely used and accepted for verifying a person's identity. Current automatic signature-based biometric systems typically require five, ten, or even more specimens of a person's signature to learn intrapersonal variability sufficient to provide an accurate verification of the individual's identity. To mitigate this drawback, this paper proposes a procedure for training with only a single reference signature. Our strategy consists of duplicating the given signature a number of times and training an automatic signature verifier with each of the resulting signatures. The duplication scheme is based on a sigma lognormal decomposition of the reference signature. Two methods are presented to create human-like duplicated signatures: the first varies the strokes' lognormal parameters (stroke-wise) whereas the second modifies their virtual target points (target-wise). A challenging benchmark, assessed with multiple state-of-the-art automatic signature verifiers and multiple databases, proves the robustness of the system. Experimental results suggest that our system, with a single reference signature, is capable of achieving a similar performance to standard verifiers trained with up to five signature specimens.
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