Towards an Automatic On-Line Signature Verifier Using Only One Reference Per Signer

被引：0

作者：

Diaz, Moises ^{[1
]}

Fischer, Andreas ^{[2
,3
,4
]}

Plamondon, Rejean ^{[2
]}

Ferrer, Miguel A. ^{[1
]}

机构：

[1] Univ Las Palmas Gran Canaria, IDeTIC Inst, Las Palmas Gran Canaria, Las Palmas, Spain

[2] Ecole Polytech Montreal, Lab Scribens, Montreal, PQ, Canada

[3] Univ Fribourg, DIUF Dept, CH-1700 Fribourg, Switzerland

[4] Univ Appl Sci & Arts Western, iCoSys Inst, Delemont, Switzerland

来源：

2015 13TH IAPR INTERNATIONAL CONFERENCE ON DOCUMENT ANALYSIS AND RECOGNITION (ICDAR) | 2015年

关键词：

VERIFICATION; REPRESENTATION;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

What can be done with only one enrolled real handwritten signature in Automatic Signature Verification (ASV)? Using 5 or 10 signatures for training is the most common case to evaluate ASV. In the scarcely addressed case of only one available signature for training, we propose to use modified duplicates. Our novel technique relies on a fully neuromuscular representation of the signatures based on the Kinematic Theory of rapid human movements and its Sigma-Lognormal model. This way, a real on-line signature is converted into the Sigma-Lognormal model domain. The model parameters are then varied to generate new duplicated signatures.

引用

页码：631 / 635

页数：5

共 20 条

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