New Approach of Feature Extraction Method Based on the Raw form and his Skeleton for Gujarati Handwritten Digits Using Neural Networks Classifier

dc.contributor.author	Moro, Kamal
dc.contributor.author	Fakir, Mohammed
dc.contributor.author	Bouikhalene, Belaid
dc.contributor.author	El Yachi, Rachid
dc.contributor.author	El Kessab, Bader Dinne
dc.date.accessioned	2016-01-06T11:16:09Z
dc.date.available	2016-01-06T11:16:09Z
dc.date.issued	2014
dc.identifier.issn	1221-454X
dc.identifier.uri	http://10.11.10.50/xmlui/handle/123456789/3789
dc.description	The Annals of "Dunarea de Jos" University of Galati	en_US
dc.description.abstract	This paper presents an optical character recognition (OCR) system for Gujarati handwritten digits. One may find so much of work for latin writing, arabic, chines, etc. but Gujarati is a language for which hardly any work is traceable especially for handwritten characters. Here in this work we have proposed a method of feature extraction based on the raw form of the character and his skeleton and we have shown the advantage of using this method over other approaches mentioned in this article.	en_US
dc.language.iso	en	en_US
dc.publisher	"Dunarea de Jos" University of Galati	en_US
dc.subject	Optical character recognition	en_US
dc.subject	neural network	en_US
dc.subject	feature extraction	en_US
dc.subject	Gujarati handwritten digits	en_US
dc.title	New Approach of Feature Extraction Method Based on the Raw form and his Skeleton for Gujarati Handwritten Digits Using Neural Networks Classifier	en_US
dc.type	Article	en_US