%0 Journal Article
	%A Inam Shamsher and  Zaheer Ahmad and  Jehanzeb Khan Orakzai and  Awais Adnan
	%D 2007
	%J International Journal of Aerospace and Mechanical Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 10, 2007
	%T OCR For Printed Urdu Script Using Feed Forward Neural Network
	%U https://publications.waset.org/pdf/11206
	%V 10
	%X This paper deals with an Optical Character Recognition
system for printed Urdu, a popular Pakistani/Indian script and is the
third largest understandable language in the world, especially in the
subcontinent but fewer efforts are made to make it understandable to
computers. Lot of work has been done in the field of literature and
Islamic studies in Urdu, which has to be computerized. In the
proposed system individual characters are recognized using our own
proposed method/ algorithms. The feature detection methods are
simple and robust. Supervised learning is used to train the feed
forward neural network. A prototype of the system has been tested on
printed Urdu characters and currently achieves 98.3% character level
accuracy on average .Although the system is script/ language
independent but we have designed it for Urdu characters only.
	%P 2986 - 2989