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Proceedings Paper

Analysis and improvement of directional element feature for off-line handwritten Chinese character recognition
Author(s): Youbin Chen; Youshou Wu; J. Ross Beveridge
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Paper Abstract

Pat work has shown the directional element feature to be useful for off-line recognition of handwritten Chinese characters. This paper presents refinements to this approach that significantly improve recognition performance. These refinements do the following: 1) assign fuzzy attributes to stroke edge pixels, 2) divide the character image into fuzzy membership cells, 3) smooth saw-toothed edges, 4) enhance information at the boundary of the character image, and 5) enhance horizontal and vertical stroke edges. The first two compensate for variations in stroke position, length inclination and width. Smoothing can correct some aliasing and dropout problems in the character images. The latter two emphasize the more important aspects of a character image. All refinements improve recognition, and when used together, they increase performance by about 10 percent: from 84.15 percent to 94.09 percent on a set of 3,755 Chinese characters. Experiments over all subsets of refinements are included. While not all refinements lead to equal improvement, all are necessary to achieve the highest level of recognition.

Paper Details

Date Published: 1 April 1998
PDF: 9 pages
Proc. SPIE 3305, Document Recognition V, (1 April 1998); doi: 10.1117/12.304620
Show Author Affiliations
Youbin Chen, Tsinghua Univ. (China) and Colorado State Univ. (United States)
Youshou Wu, Tsinghua Univ. (China)
J. Ross Beveridge, Colorado State Univ. (United States)

Published in SPIE Proceedings Vol. 3305:
Document Recognition V
Daniel P. Lopresti; Jiangying Zhou, Editor(s)

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