Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/37181
Title: Static and dynamic synthesis of bengali and devanagari signatures
Authors: Ferrer Ballester, Miguel Ángel 
Chanda, S.
Díaz Cabrera, Moisés 
Banerjee, C.K.
Majumdar, A.
Carmona-Duarte, Cristina 
Acharya, P.
Pal, U.
Keywords: 120325 Diseño de sistemas sensores
metadata.dc.subject.other: Biometrics
Handwritten signature recognition
Handwritten signature synthesis
Indian scripts
Motor equivalence model
Issue Date: 2017
Journal: IEEE Transactions on Cybernetics 
Abstract: Developing an automatic signature verification system is challenging and demands a large number of training samples. This is why synthetic handwriting generation is an emerging topic in document image analysis. Some handwriting synthesizers use the motor equivalence model, the well-established hypothesis from neuroscience, which analyses how a human being accomplishes movement. Specifically, a motor equivalence model divides human actions into two steps: 1) the effector independent step at cognitive level and 2) the effector dependent step at motor level. In fact, recent work reports the successful application to Western scripts of a handwriting synthesizer, based on this theory. This paper aims to adapt this scheme for the generation of synthetic signatures in two Indic scripts, Bengali (Bangla), and Devanagari (Hindi). For this purpose, we use two different online and offline databases for both Bengali and Devanagari signatures. This paper reports an effective synthesizer for static and dynamic signatures written in Devanagari or Bengali scripts. We obtain promising results with artificially generated signatures in terms of appearance and performance when we compare the results with those for real signatures.
URI: http://hdl.handle.net/10553/37181
ISSN: 2168-2267
DOI: 10.1109/TCYB.2017.2751740
Source: IEEE Transactions on Cybernetics [ISSN 2168-2267], p. 1-12
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