Journal of Computer Science

FEED FORWARD BACK PROPAGATION NEURAL NETWORK BASED CHARACTER RECOGNITION SYSTEM FOR TAMIL PALM LEAF MANUSCRIPTS

J. Ramya and B. Parvathavarthini

DOI : 10.3844/jcssp.2014.660.670

Journal of Computer Science

Volume 10, Issue 4

Pages 660-670

Abstract

Optical character recognition refers to the process of translating segmented hand-written images or typewritten images into machine editable text. In this study, we propose a Tamil palm leaf manuscripts character recognition system using FFBNN technology. First the palm leaf manuscripts characters are segmented by exploiting the sliding window and adaptive histogram calculation. Afterwards, these segmented characters are assembled and then stored in a database. To accomplish the character recognition process, the characters thus stored in the database are learn by Feed Forward Back Propagation Neural Network (FFBNN). Ten set of Tamil palm leaf manuscripts are utilized to evaluate the performance of proposed FFBNN based character recognition system. The results show the effectiveness of proposed character recognition system in recognizing the palm leaf manuscripts characters and the achieved improvement in character recognition shows accuracy of 90%. The performance of the proposed FFBNN based character recognition system is evaluated by changing the number hidden layers for ten set of Tamil palm leaf manuscripts."

Copyright

© 2014 J. Ramya and B. Parvathavarthini. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.