Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/43950
Title: Applying forensic features on writer identification
Authors: Travieso González, Carlos Manuel 
Alonso, Jesus B. 
Vasquez, Jose L.
Dutta, Malay Kishore
Singh, Anushikha
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: Writing , Feature extraction , Signal processing , Signal processing algorithms , Artificial neural networks , Proposals , Indexes, handwritten identification , image processing , pattern recognition
Issue Date: 2017
Journal: 2017 4th International Conference on Signal Processing and Integrated Networks, SPIN 2017
Conference: 4th International Conference on Signal Processing and Integrated Networks, SPIN 2017 
Abstract: 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
Source: 2017 4th International Conference on Signal Processing and Integrated Networks, SPIN 2017 (8050015), p. 572-577
Appears in Collections:Actas de congresos
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