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SYRIAC Character Recognition System Using Back Propagation Neural Network

Author : Basima Z.Yacob, Majd S. Mati and Danny T. Baito

Pages : 2053-2056
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The Syriac language is one of the Semitic languages that is being spoken in Iraq, Syria, Turkey and Iran by Assyrians. It’s an ancient language, one of the rarest and oldest in the world. In this paper A Syriac character recognition system using Back propagation Neural Network is proposed. A pre-processing step is implemented to separate each character from the others. After that a feature extraction process is applied on each character to obtain the invariant moments. Back propagation neural network is trained on invariant moments of East Syriac alphabet, and tested on these characters to verify each character image belongs to which type of character. This is done by using visual C#.

Keywords: Neural networks, Syriac alphabet, invariant moments, Back Prorogation Neural Network.

Article published in International Journal of Current  Engineering  and Technology, Vol.3,No.5(Dec- 2013)




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