A neural network approach to online Devanagari handwritten character recognition

Abstract

This paper proposes a neural network based framework to classify online Devanagari characters into one of 46 characters in the alphabet set. The uniqueness of this work is three-fold: (1) The feature extraction is just the Discrete Cosine Transform of the temporal sequence of the character points (utilizing the nature of online data input). We show that if used right, a simple feature set yielded by the DCT can be very reliable for accurate recognition of handwriting, (2) The mode of character input is through a computer mouse, and (3) We have built the online handwritten database of Devanagari characters from scratch, and there are some unique features in the way we have built up the database. Lastly, the testing has been carried on 2760 characters, and recognition rates of up to 97.2% are achieved.