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Generation of Handwritten Characters with Bayesian network based On-line Handwriting Recognizers
Edinburgh, Scotland August 03-August 06
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDAR.2003.1227809Seventh International Conference on D ...
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Hyunil Choi, KAIST
Jin H. Kim, KAIST
In this paper, we propose a new character generation method from on-line handwriting recognizers based on Bayesian networks. On-line handwriting recognizers are trained with handwriting samples from many writers. Then, character shapes are generated from given texts by searching the most probable input point sequences. Since Bayesian network based classifiers have large number of parameters for modeling components and their relationships, they generate more natural character shapes than various kinds of hidden Markov models.
Citation:
Hyunil Choi, Sung-Jung Cho, Jin H. Kim, "Generation of Handwritten Characters with Bayesian network based On-line Handwriting Recognizers," icdar, vol. 2, pp.995, Seventh International Conference on Document Analysis and Recognition (ICDAR'03) - Volume 2, 2003
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