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Developing handwriting recognition systems that are fast and highly reliable is a challenging problem that has become increasingly relevant following the broad acceptance of hand-held devices that use pen based handwriting inputs. Generative classifiers offer a promising solution in combination with discriminative classifiers for addressing this challenge. This paper describes a novel generative classifier - Active-DTW, that combines Active Shape Models with Elastic Matching. Experimental results show that the Active-DTW classifier shows substantial promise as a generative classifier.