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Nonlinear Active Handwriting Models and Their Applications to Handwritten Chinese Radical Recognition
Edinburgh, Scotland August 03-August 06
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDAR.2003.1227722Seventh International Conference on D ...
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G. S. Ng, Nanyang Technological University
D. Shi, Nanyang Technological University
S. R. Gunn, University of Southampton
R. I. Damper, University of Southampton
This paper proposes active handwriting models, in which kernel principal component analysis is applied to capture nonlinear handwriting variations. In the recognition phase, the chamfer distance transform and a dynamic tunnelling algorithm (DTA) are employed to search for the optimal shape parameters. The proposed methodology is successfully applied to a novel radical decomposition approach to the challenging problem of handwritten Chinese character recognition.
Citation:
G. S. Ng, D. Shi, S. R. Gunn, R. I. Damper, "Nonlinear Active Handwriting Models and Their Applications to Handwritten Chinese Radical Recognition," icdar, vol. 1, pp.534, Seventh International Conference on Document Analysis and Recognition (ICDAR'03) - Volume 1, 2003
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