Share Email Print
cover

Proceedings Paper

Segmentation of knowledge-radicals for on-line handwritten Chinese characters
Author(s): Chao-Hao Lee; Ming-Wen Chang; Hon-Fai Yau; Bor-Shenn Jeng; Dung-Ming Shieh; Char-Shin Miou; Chi-Jain Wen
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

In this paper, a segmentation method of knowledge-radicals for on-line handwritten Chinese characters (OLHCC) is proposed. Using the methods of finding local minimum and finding minimum of sum in local regions, some segmentation lines are obtained. We use a trick called `line segment shortening' to improve the above mentioned methods if overlapped radicals exist in a character. Based on the common writing habits of people, the decision algorithms are proposed to identify the correctness of segmentation lines. Our experimental results are conducted on ten databases of 5401 frequently used Chinese characters that users wrote according to their habits. An average suitable segmentation rate of more than 94% has been obtained, which shows that our algorithm is reliable.

Paper Details

Date Published: 21 September 1994
PDF: 8 pages
Proc. SPIE 2298, Applications of Digital Image Processing XVII, (21 September 1994); doi: 10.1117/12.186558
Show Author Affiliations
Chao-Hao Lee, National Central Univ. (Taiwan)
Ming-Wen Chang, National Central Univ. (Taiwan)
Hon-Fai Yau, National Central Univ. (Taiwan)
Bor-Shenn Jeng, National Central Univ. and Ministry of Transportation and Communications (Taiwan)
Dung-Ming Shieh, National Central Univ. (Taiwan)
Char-Shin Miou, National Central Univ. and Ministry of Transportation and Communications (Taiwan)
Chi-Jain Wen, National Central Univ. (Taiwan)


Published in SPIE Proceedings Vol. 2298:
Applications of Digital Image Processing XVII
Andrew G. Tescher, Editor(s)

© SPIE. Terms of Use
Back to Top