Handwritten Hangul Character Recognition with Hierarchical Stochastic Character Representation

Seventh International Conference on Document Analysis and Recognition (ICDAR'03) - Volume 1 p. 212
Handwritten Hangul Character Recognition with Hierarchical Stochastic Character Representation
Kyung-Won Kang, KAIST
Jin H. Kim, KAIST

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DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDAR.2003.1227661
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Abstract
In structural character recognition, a character is usually viewed as a set of strokes and the spatial relationships between them. In this paper, we propose a stochastic modeling scheme by which strokes as well as relationships are represented by utilizing the hierarchical characteristics of target characters. Based on the proposed scheme, a handwritten Hangul (Korean) character recognition system is developed. The effectiveness of the proposed scheme is shown through experimental results conducted on a public database.
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Citation: Kyung-Won Kang, Jin H. Kim, "Handwritten Hangul Character Recognition with Hierarchical Stochastic Character Representation," icdar, p. 212, Seventh International Conference on Document Analysis and Recognition (ICDAR'03) - Volume 1, 2003

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