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Proceedings Paper

Measures for structural and global shape description in handwritten Kanji character recognition
Author(s): Minoru Mori; Toru Wakahara; Kenji Ogura
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Paper Abstract

This paper proposes new features for recognizing handwritten Japanese Kanji characters. Many feature extraction methods have been studied for Kanji. In particular, stroke directional features are effective if the Kanji are well formed. Directional features are local shape descriptions of individual strokes and so are not robust against shape distortion, in particular, slanting, rotation, and the fluctuation in stroke direction seen in freely handwritten characters. Against this distortion, the 2D relative arrangement of constituent strokes is rather effective as a structural and global shape description. We focus on this fact and derive new features for measuring the 2D relationship between strokes. We derive new measures that express the 2D relationship from directional features of adjacent strokes, and use these as new features. The new features express the relative angle and the relative position of adjacent strokes as a structural and global shape description. Experiments show that the proposed new measures achieve very high recognition rates of about 95 percent for a data set in the square style and about 80 percent for a data set in the free style. These represent a reduction of about 20 percent in the error rates for both data sets achieved with the original directional features.

Paper Details

Date Published: 1 April 1998
PDF: 9 pages
Proc. SPIE 3305, Document Recognition V, (1 April 1998); doi: 10.1117/12.304621
Show Author Affiliations
Minoru Mori, NTT Human Interface Labs. (Japan)
Toru Wakahara, NTT Human Interface Labs. (Japan)
Kenji Ogura, NTT Human Interface Labs. (Japan)

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

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