Identificador persistente para citar o vincular este elemento:
http://hdl.handle.net/10553/136826
Título: | Online signature verification based on the lagrange formulation with 2D and 3D robotic models | Autores/as: | Diaz, Moises Ferrer, Miguel A. Gil, Juan M. Rodriguez, Rafael Zhang, Peirong Jin, Lianwen |
Clasificación UNESCO: | 331117 Equipos de verificación 330405 Sistemas de reconocimiento de caracteres |
Palabras clave: | Online signature verification Generalized coordinates Torques Biometrics |
Fecha de publicación: | 2025 | Proyectos: | Robusteciendo Las Biometrías Del Movimiento de la Mano Mediante la Síntesis de Su Timbre Usando Métodos Computacionalesy Robóticos Detección de Movimientos Generados por Humanos y Máquinas. |
Publicación seriada: | Pattern Recognition | Resumen: | Online Signature Verification commonly relies on function-based features, such as time-sampled horizontal and vertical coordinates, as well as the pressure exerted by the writer, obtained through a digitizer. Although inferring additional information about the writer's arm pose, kinematics, and dynamics based on digitizer data can be useful, it constitutes a challenge. In this paper, we tackle this challenge by proposing a new set of features based on the dynamics of online signatures. These new features are inferred through a Lagrangian formulation, obtaining the sequences of generalized coordinates and torques for 2D and 3D robotic arm models. By combining kinematic and dynamic robotic features, our results demonstrate their significant effectiveness for online automatic signature verification and achieving state-of-the-art results when integrated into deep learning models. | URI: | http://hdl.handle.net/10553/136826 | ISSN: | 0031-3203 | DOI: | 10.1016/j.patcog.2025.111581 | Fuente: | Pattern Recognition [ISSN 0031-3203], v. 164, (Agosto 2025) |
Colección: | Artículos |
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