Deep learning approach to generate offline handwritten signatures based on online samples
Author:
Affiliation:
1. Polytechnic School, University of PernambucoRecifeBrazil
2. Dipartimento di InformaticaUniversità degli Studi di BariBariItaly
Publisher
Institution of Engineering and Technology (IET)
Subject
Computer Vision and Pattern Recognition,Signal Processing,Software
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-bmt.2018.5091
Reference27 articles.
1. Automatic Signature Verification: The State of the Art
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3. On‐line signature verification using vertical signature partitioning;Cpałka K.;Expert Syst. Appl.,2014
4. Viard‐Gaudin C. Lallican P.M. Knerr S. et al. : ‘The IRESTE on/off (IRONOFF) dual handwriting database’.Proc. Fifth Int. Conf. Document Analysis and Recognition 1999 ICDAR'99 Bangalore India 1999 pp.455–458
5. Herrero J.G. Fierrez J. Díaz M.M. et al. : ‘Synthetic generation of handwritten signatures based on spectral analysis’.Proc. SPIE – The Int. Society for Optical Engineering. Society of Photo‐Optical Instrumentation Engineers Orlando USA 2009
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