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ICPR
2008
IEEE

Radical based fine trajectory HMMs of online handwritten characters

12 years 6 months ago
Radical based fine trajectory HMMs of online handwritten characters
We study models that characterize pen trajectories of online handwritten characters in a fine manner. We propose radical based fine trajectory hidden Markov models (HMMs), which adopt radicals as basic units, and a multi-path HMM topology that emits observations with multi-space distributions (MSD) is built for each radical. Meanwhile, various stroke orders, writing styles and realness of sub-strokes are reasonably modeled. The radical based fine trajectory HMMs lead to handwriting recognition with effective prediction, and their generative nature can be utilized for a novel handwriting synthesis framework. Experimental show that along with the model precision increasing, about 50% recognition error can be reduced, and the fine models can generate decent character samples.
Peng Liu, Lei Ma, Frank K. Soong
Added 30 May 2010
Updated 30 May 2010
Type Conference
Year 2008
Where ICPR
Authors Peng Liu, Lei Ma, Frank K. Soong
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