Peripheral and global features for use in coarse classification of Chinese characters
Identifieur interne : 002378 ( Main/Exploration ); précédent : 002377; suivant : 002379Peripheral and global features for use in coarse classification of Chinese characters
Auteurs : Kuo-Sen Chou [République populaire de Chine] ; Kuo-Chin Fan [République populaire de Chine] ; Tzu-I Fan [République populaire de Chine]Source :
- Pattern Recognition [ 0031-3203 ] ; 1996.
Abstract
In this paper, a simple and effective approach to the coarse classification of handwritten Chinese characters is proposed. In our approach, a Chinese character is characterized by string representation using periphery and global feature vectors. The peripheral features include four strings to represent the structure of segments in top, bottom, left, and right directions. The global features include the number of horizontal segments in the top direction and bottom direction, and the number of stroke segments in a character. In addition, a scoring-based coarse classification scheme is devised in choosing the proper candidate characters. Twenty sets of Chinese characters (5401 characters/set) are tested. The number of candidate characters is reduced from 5401 to about 80 with the error rate less than 1.2% in average. Experimental results reveal the feasibility of the proposed approach in classifying Chinese characters.
Url:
DOI: 10.1016/S0031-3203(96)00090-8
Affiliations:
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In our approach, a Chinese character is characterized by string representation using periphery and global feature vectors. The peripheral features include four strings to represent the structure of segments in top, bottom, left, and right directions. The global features include the number of horizontal segments in the top direction and bottom direction, and the number of stroke segments in a character. In addition, a scoring-based coarse classification scheme is devised in choosing the proper candidate characters. Twenty sets of Chinese characters (5401 characters/set) are tested. The number of candidate characters is reduced from 5401 to about 80 with the error rate less than 1.2% in average. Experimental results reveal the feasibility of the proposed approach in classifying Chinese characters.</div></front></TEI><affiliations><list><country><li>République populaire de Chine</li></country></list><tree><country name="République populaire de Chine"><noRegion><name sortKey="Chou, Kuo Sen" sort="Chou, Kuo Sen" uniqKey="Chou K" first="Kuo-Sen" last="Chou">Kuo-Sen Chou</name></noRegion><name sortKey="Fan, Kuo Chin" sort="Fan, Kuo Chin" uniqKey="Fan K" first="Kuo-Chin" last="Fan">Kuo-Chin Fan</name><name sortKey="Fan, Tzu I" sort="Fan, Tzu I" uniqKey="Fan T" first="Tzu-I" last="Fan">Tzu-I Fan</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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