Handwritten Numeral Recognition by Model Reconstruction Based on Manifold Learning

摘要：

To overcome the instability of handwritten character caused by different writing style,a novel approach of model reconstruction based on manifold learning is proposed in this paper.Traditional recognition method reduce dimension firstly,and then recognize the character in the reduced feature space.In this paper,we present a method based on reconstruction LLE.The algorithm first reduce dimension in each class.Then reconstruct the character in each class.Finally character recognition is then conducted based on the error analysis of reconstruction model.The algorithm proposed in this paper is tested on the characters in MlNST character database and the experimentaI results demonstrate that the method can effectively improve the recognition rate of handwritten digits and provide a new approach to the research of handwritten digits recognition.

作者: Wu Wei Yang Xiaomin He Xiaohai Chen Mo

会议类型: 国际会议

会议名称: The International Conference Information Computing and Automation(2007国际信息计算与自动化会议)

会议地点: 成都

会议语种:英文

页码: 167-170

在线出版日期: 2007-12-19（万方平台首次上网日期，不代表论文的发表时间）