期刊
PATTERN RECOGNITION
卷 43, 期 7, 页码 2582-2589出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.patcog.2010.01.008
关键词
Optical character recognition; Feed forward neural network; Feature abstraction; Gujarati handwritten digits; Classification
This paper deals with an optical character recognition (OCR) system for handwritten Gujarati numbers. One may find so much of work for Indian languages like Hindi, Kannada, Tamil, Bangala, Malayalam, Gurumukhi etc, but Gujarati is a language for which hardly any work is traceable especially for handwritten characters. Here in this work a neural network is proposed for Gujarati handwritten digits identification. A multi layered feed forward neural network is suggested for classification of digits. The features of Gujarati digits are abstracted by four different profiles of digits. Thinning and skew-correction are also done for preprocessing of handwritten numerals before their classification. This work has achieved approximately 82% of success rate for Gujarati handwritten digit identification. (C) 2010 Elsevier Ltd. All rights reserved.
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