SVM-Based Handwritten Chinese Character Recognition

摘要：

In this paper, a new recognition method of handwritten Chinese characters by support vector machine is presented. SVM operates on the principle of structure risk minimization and hence produces better generalization ability. The problems to be solved while applying SVM in Chinese character recognition are addressed at first, and then a two stage of recognition scheme is suggested. Finally, experimental results on 100 categories of character from 70 sets of sample are given to show the efficiency of SVM.

关键词： support vector machine handwritten Chinese character recognition feature extraction.

作者: Xue Gao Lian-Wen Jin Jun-Xun Yin Jian-Cheng Huang

作者单位: Department of Electronics and Communication Engineering South China University of Technology, Guangz Motorola China Research Center, Shanghai 200002, P. R. China

会议类型: 国际会议

会议名称: 8th International Conference on Neural Information Processing(ICONIP 2001)(第八届国际神经信息处理大会)

会议地点: 上海

会议语种:英文

页码: 1393-1397

在线出版日期: 2001-11-14（万方平台首次上网日期，不代表论文的发表时间）