|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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