The Community for Technology Leaders
RSS Icon
Subscribe
Issue No.05 - May (1998 vol.20)
pp: 556-561
ABSTRACT
<p>Abstract—One of the most challenging topics is the recognition of Chinese handwriting, especially offline recognition. In this paper, an offline recognition system based on multifeature and multilevel classification is presented for handwritten Chinese characters. Ten classes of multifeatures, such as peripheral shape features, stroke density features, and stroke direction features, are used in this system. The multilevel classification scheme consists of a group classifier and a five-level character classifier, where two new technologies, overlap clustering and Gaussian distribution selector, are developed. Experiments have been conducted to recognize 5,401 daily-used Chinese characters. The recognition rate is about 90 percent for a unique candidate, and 98 percent for multichoice with 10 candidates.</p>
INDEX TERMS
Offline Chinese handwriting recognition, multifeature, multilevel classification, overlap clustering, Gaussian distribution selector.
CITATION
Yuan Y. Tang, Lo-Ting Tu, Jiming Liu, Seong-Whan Lee, Win-Win Lin, Ing-Shyh Shyu, "Offline Recognition of Chinese Handwriting by Multifeature and Multilevel Classification", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.20, no. 5, pp. 556-561, May 1998, doi:10.1109/34.682186
19 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool