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The fact that English language is a universal language, so it is necessary to propose a computerized ways to recognize the texts written in English language, which will simplifies the reading of any text, treat it, and deal with it in a least possible time. The BAM (Bidirectional Associative Memory) network was used to recognize the printed English letters, because it process the small size images of letters in an easy way, also BAM is working in two ways (forward and backward) and store the weights without any amendment, therefore BAM is considered as one of the networks of education controller (Supervised learning). The recognition of the printed English text was done using the network BAM, while the printed English text was entered to the computer using the scanner, also BAM network used to recognize the letters that have some noise and after training; it gives successful results of recognition about 84.6%. The aim of this research is to segment and recognize the printed English text, wither it is clear or it have some noise, Matlab R2008a language is used to accomplish this work.

Scansion Text Written in English language and Recognized Printed English Character using Bidirectional Associative Memory Network