Latin Character Recognition using Neural Networks

The aim of this work is to recognize the printed Latin's characters. In this work two methods for constructing the feature space are used. These methods are Variance and Fractal dimension methods, as a result they have real values for every character in the Latin's language, and from these values they constructed the feature space extractions for every character in the Latin's language. After that, these features are given to the Back Propagation network for recognizing the characters.
The result is a highest recognition for the characters is obtained, it is about 82.75% characters while the unrecognized characters are 17.25.