An Attempt to Recognize Handwritten Tamil Character Using Kohonen SOM

This paper presents a new approach of Kohonen neural network based Self Organizing Map (SOM) algorithm for Tamil Character Recognition. Which provides much higher performance than the traditional neural network. Approaches: Step 1: It describes how a system is used to recognize a hand written Tamil characters using a classification approach. The aim of the pre-classification is to reduce the number of possible candidates of unknown character, to a subset of the total character set. This is otherwise known as cluster, so the algorithm will try to group similar characters together. Step 2: Members of pre-classified group are further analyzed using a statistical classifier for final recognition. A recognition rate of around 79.9% was achieved for the first choice and more than 98.5% for the top three choices. The result shows that the proposed Kohonen SOM algorithm yields promising output and feasible with other existing techniques.