Clustering-based Approach with Dynamic Time Warping for Thai On-line Handwriting Recognition

Abstract

On-line handwriting recognition becomes important since hand-held devices become widely used. However, we still are lacking of an efficient recognition system for writer independent unconstrained Thai handwritten characters. In this paper, we propose the use of clustering algorithm using dynamic time warping as a similarity measure to analyze and categorize users's handwriting in order to construct a set of templates for each class of characters. Then, those templates are used to classify unknown handwritten sequences. To evaluate the proposed system, the experiment on the collected natural Thai handwriting were conducted. The experimental results showed the efficiency of the system.