DocumentCode :
2629231
Title :
An Arabic character recognition system using neural network
Author :
Sanossian, Hermineh Y Y
Author_Institution :
Comput. Sci. Dept., Mutah Univ., Karak, Jordan
fYear :
1996
fDate :
4-6 Sep 1996
Firstpage :
340
Lastpage :
348
Abstract :
An optical character recognition system, which uses a multilayer perceptron classifier, is described. A new approach for the classification of Arabic characters is presented. The technique used is invariant to translation, scale and rotation. Present day artificial neural network (ANN) architecture for invariant character recognition is too complex for our present technology. An alternative procedure is to preprocess the input data and represent them in another form which is invariant to geometrical changes. The advantage of using such a method is that the number of input features is reduced considerably
Keywords :
feature extraction; image classification; multilayer perceptrons; optical character recognition; Arabic character recognition system; input features; invariant character recognition; multilayer perceptron classifier; optical character recognition system; Artificial neural networks; Character recognition; Computer science; Data preprocessing; Feature extraction; Multilayer perceptrons; Neural networks; Optical character recognition software; Optical computing; Pattern recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks for Signal Processing [1996] VI. Proceedings of the 1996 IEEE Signal Processing Society Workshop
Conference_Location :
Kyoto
ISSN :
1089-3555
Print_ISBN :
0-7803-3550-3
Type :
conf
DOI :
10.1109/NNSP.1996.548364
Filename :
548364
Link To Document :
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