In this paper we propose a stroke recognition method for online handwritten Hangul recognition system. The proposed system extracts a distance-dependent curvature from two-dimensional original stroke data and achieves elastic matching between distance-dependent curvatures of reference and test characters. Elastic curvature matching has lower computational requirement than existing 2D-to-2D elastic matching. Each recognized stroke from the elastic curvature matching is converted into a Hangul syllable and additional position information is added to improve performance of the recognizer in this process.
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