Neural Network with Madaline for Machine Printed English Character Recognition

ABSTRACT The recognition of optical characters is known to be one of the earliest applications of Artificial Neural Networks, which partially emulate human thinking in the domain of artificial intelligence. In this research the application of neural networks to the problem of identifying English machine printed characters in an automated manner is developed. A preprocessing step is implemented to separate each character from the others. After that a feature extraction process is applied on each character to obtain the minimum nodes by using Mean, Standard Deviation, and Variance. Madaline neural network is trained on a 26 alphabetical English characters with a standard font and size. And tested on these characters to verify each character image belongs to which type of character. This is done by using MATLAB®2008a