Identificador persistente para citar o vincular este elemento:
http://hdl.handle.net/10553/69928
| Título: | Analysis of the transformed contour in the writer identification | Autores/as: | Travieso González, Carlos Manuel Vásquez-Nuñez, Jose Luis Briceno-Lobo, Juan Carlos |
Clasificación UNESCO: | 240401 Bioestadística | Palabras clave: | Biometrics Classification Systems Feature Transformation Handwritten Writing Offline Approach, et al. |
Fecha de publicación: | 2019 | Editor/a: | Noida | Publicación seriada: | 2019 6Th International Conference On Signal Processing And Integrated Networks (Spin) | Conferencia: | 6th International Conference on Signal Processing and Integrated Networks, SPIN 2019 | Resumen: | This work shows an approach for the writer identification using off-line handwritten writing. The contour of handwritten words is calculated. That feature is transformed by a Hidden Markov Model, in order to get a hyperdimensionality of new features. Later, a support vector machine classifier is applied to analyze the grade of discrimination. The approach reaches an accuracy between 98,60% and 100%, according to the type of word. This proposal presents a robust and novel system for the based-writing identification in comparison versus the state-of-the-art; and shows the study of its efficiency according to different off-line handwritten words. | URI: | http://hdl.handle.net/10553/69928 | ISBN: | 9781728113791 | DOI: | 10.1109/SPIN.2019.8711588 | Fuente: | 2019 6th International Conference on Signal Processing and Integrated Networks, SPIN 2019, p. 195-199 |
| Colección: | Actas de congresos |
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