Abstract:
Genetic Algorithms have been quite successfully applied to a number of problems. The
most outstanding results come from the field of parameter optimization, where the coding
is rather straightforward. A few attempts were made to its application to pattern
recognition in the framework of supervised learning technique.
In this endeavour, A character recognition system using Genetic Algorithm has been
developed. The system is intended to recognize printed Bengali characters. The model
proposed for this system consists of a preprocessor followed by a Genetic Algorithm
classifier. At preprocessing phase, projection from each active bit of a pattern has been
scaled and translated to fit a standard size. The second part of the system comprises a
Genetic Algorithm classifier which generates a set of rules based on the extracted
features of the patterns. The rules are generated in such a way that only the distinctive
features of a pattern are reflected in the rule. After being trained using a training set of
character patterns, the system has been able to classifY test character patterns correctly.
The proposed model has been tested with two complete character sets of Bengali alphabet
and rigorous experiments have been carried out to see how the performance of Genetic
Algorithm as a classifier varies at different parameter settings in the context of Bengali
character recognition.
