Identificador persistente para citar o vincular este elemento:
http://hdl.handle.net/10553/43950
| Título: | Applying forensic features on writer identification | Autores/as: | Travieso González, Carlos Manuel Alonso, Jesus B. Vasquez, Jose L. Dutta, Malay Kishore Singh, Anushikha |
Clasificación UNESCO: | 3307 Tecnología electrónica | Palabras clave: | Writing , Feature extraction , Signal processing , Signal processing algorithms , Artificial neural networks , Proposals , Indexes, handwritten identification , image processing , pattern recognition | Fecha de publicación: | 2017 | Publicación seriada: | 2017 4th International Conference on Signal Processing and Integrated Networks, SPIN 2017 | Conferencia: | 4th International Conference on Signal Processing and Integrated Networks, SPIN 2017 | Resumen: | This work present new parameters based on biometrie handwritten information for the writer identification. The feature extraction is developed by new algorithms based on image processing techniques. The handwritten parameters will be classified by artificial neural network and fusion strategy in order to increase the accuracy. After experiments, and using a dataset composed by 100 writers, this proposal reaches an accuracy of 82.7% | URI: | http://hdl.handle.net/10553/43950 | ISBN: | 9781509027972 | DOI: | 10.1109/SPIN.2017.8050015 | Fuente: | 2017 4th International Conference on Signal Processing and Integrated Networks, SPIN 2017 (8050015), p. 572-577 |
| Colección: | Actas de congresos |
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