Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/44045
Title: Combining different off-line handwritten character recognizers
Authors: Travieso, Carlos M. 
Alonso, Jesús B. 
Ferrer, Miguel A. 
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: Training , Handwriting recognition , Character recognition , Feature extraction , Support vector machines , Databases , Off-line handwritten recognition , Decision Fusion , OCR , Pattern Recognition
Issue Date: 2011
Journal: INES 2011 - 15th International Conference on Intelligent Engineering Systems, Proceedings
Conference: 15th International Conference on Intelligent Engineering Systems, INES 2011 
Abstract: This present work presents a recognizer based on the combination of three Support Vector Machine (SVM) classifiers whose inputs have different parameters from characters. The three approaches of feature extraction for handwritten off-line digits, capital letters and lower case letters, have been chosen for improving the combination using database NIST-SD19. We have applied pre-processing in order to achieve greater inter-class discrimination and similarity. These three feature extractions are based on Kirsch masks with and without slant correction and Fourier elliptic descriptors.
URI: http://hdl.handle.net/10553/44045
ISBN: 9781424489565
DOI: 10.1109/INES.2011.5954765
Source: INES 2011 - 15th International Conference on Intelligent Engineering Systems, Proceedings (5954765), p. 315-318
Appears in Collections:Actas de congresos
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