Period Prediction System for Tamil Epigraphical Scripts Based on Support Vector Machine

Tamil is one of the ancient languages of the world with records in the language dating back over two millennia. Epigraphical scripts are the inscription written on various materials and the study of it is vital in knowing the civilized past and hence classification of character belonging to various periods is imperative before using the character bank of the particular period. Therefore a system is proposed for prediction of the period and it is being done by examining a few character referred to as test characters in Tamil language. These test characters are sampled from the script automatically and matched with the characters available for different periods using machine intelligence. The proposed system here has various modules like binarization, thinning, segmentation, feature extraction and finally classification and period prediction using Support Vector Machine. Its performance is most successful in differentiating between four centuries of character. The performance of the system is measured using the four parameters such as prediction rate, Correction rate, Error rate and Time taken to predict the centuries. The system achieves overall accuracy of 90.45%.