Dynamic TimeWarping Applied to Tamil Character Recognitio

This paper describes the use of dynamic time warping (DTW) for classifying handwritten Tamil characters. Since DTW can match characters of arbitrary length, it is particularly suited for this domain. We built a prototype based classifier that uses DTW both for generating prototypes and for calculating a list of nearest prototypes. Prototypes were automatically generated and selected. Two tests were performed to measure the performance of our classifier in a writer dependent, and in a writer independent setting. Furthermore, several strategies were developed for rejecting uncertain cases. Two different rejection variables were implemented and using a Monte Carlo simulation, the performance of the system was tested in various configurations. The results are promising and show that the classifier can be of use in both writer dependent and writer independent automatic recognition of handwritten Tamil characters.