New Approach of Feature Extraction Method Based on the Raw Form and his Skeleton for Gujarati Handwritten Digits using Neural Networks Classifier
Keywords:
optical character recognition, neural network, feature extraction, Gujarati handwritten digits, skeletonization, classification
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.
Published
2014-09-30
How to Cite
1.
Moro K, Fakir M, Bouikhalene B, Yachi R, El Kessab B. New Approach of Feature Extraction Method Based on the Raw Form and his Skeleton for Gujarati Handwritten Digits using Neural Networks Classifier. The Annals of “Dunarea de Jos“ University of Galati. Fascicle III, Electrotechnics, Electronics, Automatic Control, Informatics [Internet]. 30Sep.2014 [cited 5May2024];37(1):5-0. Available from: https://www.gup.ugal.ro/ugaljournals/index.php/eeaci/article/view/453
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Section
Articles
@ "Dunarea de Jos" University of Galati
