Realistic synthetic off-line signature generation based on synthetic on-line data
- 1 October 2013
- conference paper
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
Abstract
A novel method for the generation of synthetic offline signatures is presented. The proposed algorithm follows a two steps scheme: first, the raw synthetic dynamic functions of the synthetic signature are generated; second, several ink and paper models are applied to transform the on-line data to realistic static signatures. The novel approach is validated using four different publicly available databases both real and synthetic. The experimental protocol includes the comparison of both types of signatures in terms of: i) performance evaluation of two competitive and totally different verification systems; and ii) visual appearance according to human observers. The experimental results show the high similarity existing between synthetically generated and humanly produced samples, and the potential of the proposed method for the study of the signature trait.Keywords
This publication has 10 references indexed in Scilit:
- Synthetic off-line signature image generationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2013
- Synthetic on-line signature generation. Part I: Methodology and algorithmsPattern Recognition, 2012
- Synthetic on-line signature generation. Part II: Experimental validationPattern Recognition, 2012
- Robustness of Offline Signature Verification Based on Gray Level FeaturesIEEE Transactions on Information Forensics and Security, 2012
- Off-line signature verification based on grey level information using texture featuresPattern Recognition, 2011
- Development of a Sigma–Lognormal representation for on-line signaturesPattern Recognition, 2009
- On Generation and Analysis of Synthetic Iris ImagesIEEE Transactions on Information Forensics and Security, 2007
- Offline geometric parameters for automatic signature verification using fixed-point arithmeticIEEE Transactions on Pattern Analysis and Machine Intelligence, 2005
- Ink-Deposition Model: The Relation of Writing and Ink Deposition ProcessesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2004
- MCYT baseline corpus: a bimodal biometric databaseIEE Proceedings - Vision, Image, and Signal Processing, 2003