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Diagonal based feature extraction for handwritten character recognition system using neural network

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3 Author(s)
J. Pradeep ; Department of ECE, Pondicherry Engineering College, Pondicherry, India ; E. Srinivasan ; S. Himavathi

An off-line handwritten alphabetical character recognition system using multilayer feed forward neural network is described in the paper. A new method, called, diagonal based feature extraction is introduced for extracting the features of the handwritten alphabets. Fifty data sets, each containing 26 alphabets written by various people, are used for training the neural network and twenty different handwritten alphabets characters are used for testing. The proposed recognition system performs quite well yielding higher levels of recognition accuracy compared to the systems employing the conventional horizontal and vertical methods of feature extraction. This system will be suitable for converting handwritten documents into structural text form and recognizing handwritten names.

Published in:

Electronics Computer Technology (ICECT), 2011 3rd International Conference on  (Volume:4 )

Date of Conference:

8-10 April 2011