Utiliza este identificador para citar o vincular este elemento: http://hdl.handle.net/10553/37181
Títulos: Static and dynamic synthesis of bengali and devanagari signatures
Autores/as: Ferrer Ballester, Miguel Ángel 
Chanda, S.
Díaz Cabrera, Moisés 
Banerjee, C.K.
Majumdar, A.
Carmona-Duarte, Cristina 
Acharya, P.
Pal, U.
Clasificación UNESCO: 120325 Diseño de sistemas sensores
Palabras clave: Biometrics
Handwritten signature recognition
Handwritten signature synthesis
Indian scripts
Motor equivalence model
Fecha de publicación: 2017
Revistas: IEEE Transactions on Cybernetics 
Resumen: 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
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