Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/120469
Título: Impact of Writing Order Recovery in Automatic Signature Verification
Autores/as: Diaz, Moises 
Crispo, Gioele
Parziale, Antonio
Marcelli, Angelo
Ferrer, Miguel A. 
Clasificación UNESCO: 3307 Tecnología electrónica
Palabras clave: Function-Based Features
Signature Verification
Spatial Sequences
Writing Order Recovery
Fecha de publicación: 2022
Editor/a: Springer 
Publicación seriada: Lecture Notes in Computer Science 
Conferencia: 20th International Conference of the International Graphonomics Society, (IGS 2021)
Resumen: In signature verification, spatio-temporal features offer better performance than the ones extracted from static images. However, estimating spatio-temporal or spatial sequences in static images would be advantageous for recognizers. This paper studies recovered trajectories from skeleton-based images and their impact in automatic signature verification. To this aim, we propose to use a publicly available system for writing order recovery trajectory in offline signatures. Firstly, 8-connected recovered trajectories are generated from our system. Then, we evaluate their impact on the performance of baseline signature verification systems to the original trajectories. Our observations on three databases suggest that verifiers based on distributions are more suitable than those that requiring the exact order of the signatures for the off-2-on challenge.
URI: http://hdl.handle.net/10553/120469
ISBN: 9783031197444
ISSN: 0302-9743
DOI: 10.1007/978-3-031-19745-1_2
Fuente: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)[ISSN 0302-9743],v. 13424 LNCS, p. 11-25, (Enero 2022)
Colección:Actas de congresos
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