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Active-DTW : A Generative Classifier that combines Elastic Matching with Active Shape Modeling for Online Handwritten Character Recognition

Abstract : 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.
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https://hal.inria.fr/inria-00104782
Contributor : Anne Jaigu <>
Submitted on : Monday, October 9, 2006 - 2:01:15 PM
Last modification on : Thursday, December 28, 2017 - 1:58:02 PM
Long-term archiving on: : Thursday, September 20, 2012 - 11:31:09 AM

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  • HAL Id : inria-00104782, version 1

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Muralikrishna Sridha, Dinesh Mandalapu, Mehul Patel. Active-DTW : A Generative Classifier that combines Elastic Matching with Active Shape Modeling for Online Handwritten Character Recognition. Tenth International Workshop on Frontiers in Handwriting Recognition, Université de Rennes 1, Oct 2006, La Baule (France). ⟨inria-00104782⟩

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