Segmentation of On-line Cursive Handwritten Chinese Word Based on Stroke Speed Feature and Stroke Vector Feature

摘要：

On-line handwritten Chinese word recognition has recently become an important research topic in the filed of computer vision. However, the segmentation of cursive Chinese word is still an unsolved problem. In this paper, two new features, Stroke Speed Feature and Stroke Vector Feature, are proposed for the segmentation of on-line handwritten Chinese word. Analysis and experiments show that both of the features are easy to implement, with low computation complexity and encouraging correct segmentation accuracy. Furthermore, the Stroke Vector Feature outperforms traditional histogram method and we found it is especially suitable for the segmentation of cursive handwritten word where two characters touch each other or overlap.

关键词： On-line Chinese character segmentation Word recognition Stroke Vector Feature Stroke Speed Feature

作者: GUO Rui JIN LianWen

作者单位: School of Electronics and Information Engineering South China University of Technology Guangzhou, Guangdong Province, China

会议类型: 国际会议

会议名称: 2007 IEEE International Conference on Automation and Lofistics

会议地点: 山东济南

会议语种:英文

在线出版日期: 2007-08-18（万方平台首次上网日期，不代表论文的发表时间）