Using Dynamic Time Warping for Intuitive Handwriting Recognition

Abstract

This paper discusses the use of Dynamic Time Warping (DTW) for visually perceptive and intuitive character recognition. In particular in forensic document examination, techniques are required that yield results matching a human user's expectations. In our approach, the goal is to retrieve a set of best matching allographic prototypes based on a query input character. Since DTW compares each pair of closest points from two trajectories, our assumption is that it may resemble most of the pair-wise coordinate comparisons employed by humans. In order to assess our ideas, we have set up a human factors experiment in which two variants of DTW are compared to a state-ofthe- art character classifier, HCLUS. A number of 25 subjects judged the recognition results of these three classifiers for 130 queries. As a result, one particular implementation of DTW was significantly rated as the best system. Future research will combine these promising new findings with techniques that employ other distinctive features like those used by human experts. This research is embedded in the Dutch TRIGRAPH project, which pursues the design of forensic document examination techniques based on expert knowledge.