Abstract:
Recognizing characters is a problem that at first seems simple but it's
extremely difficult in practice to program a computer to do it. And yet,
automated character recognition is of vital importance in many industries,
which handle floods of paper works everyday.
In this study, a feedforward neural network based character recognition
system was implemented. The system consists of two parts. The first part is
a preprocessor, which is intended to produce a binarized, segmented, and
normalized representation of the input pattern. The preprocessed output will
then be classified by a neural network classifier trained by a
backpropagation training algorithm. Results are shov/n concerning training
data consists of characters of font styles Arial, Verdana and Times New
Roman. All are of font size 12. The system yields a 78% recognition rate on
the training data.
