| 一种新的离线手写签名识别方法 |
| |
| 引用本文： | 尹明,尹忠科,袁龙,王建英.一种新的离线手写签名识别方法[J].现代电子技术,2007,30(10):97-99. |
| |
| 作者姓名： | 尹明 尹忠科 袁龙 王建英 |
| |
| 作者单位： | 西南交通大学,信息科学与技术学院,四川,成都,610031 |
| |
| 基金项目： | 教育部回国人员科研启动资金;西南交通大学校科研和教改项目 |
| |
| 摘 要： | 脱线签名的验证较难,他仅依靠签名图像的静态信息,而书写过程中的动态信息几乎完全消失。针对脱线手写签名识别的特点,提出基于提升小波变换的特征选取方法,将传统的结构特征与统计特征有机结合起来。运用K-L变换对已提取的特征向量进行降维。最后通过支持向量机进行真伪识别。实验结果表明该算法对测试样本具有高识别率。
|
| 关 键 词： | 手写签名 提升小波 K-L变换 支持向量机(SVM) |
| 文章编号： | 1004-373X（2007）10-097-03 |
| 收稿时间： | 2006-09-27 |
| 修稿时间： | 2006-09-27 |
A New Recognition Method for Chinese Characters Image |
| |
| YIN Ming,YIN Zhongke,YUAN Long,WANG Jianying.A New Recognition Method for Chinese Characters Image[J].Modern Electronic Technique,2007,30(10):97-99. |
| |
| Authors: | YIN Ming YIN Zhongke YUAN Long WANG Jianying |
| |
| Abstract: | Identification of off-line handwritten signature is hard,because it only depends on static information,dynamic information is disappears.Aimed at the recognition characteristic of off-line handwritten signature,the feature selection method based on lifting wavelet transform is presented,and structure feature is combined with statistical feature both are conventional method.Extracted eigenvector is compressed by K-L transform.At last,true signature and forge signature are distinguished through support vector machines.The experiment results confirm given algorithm can reach satisfied identical rate for testing stylebook. |
| |
| Keywords: | handwritten signature lifting wavelet K-L transform Support Vector Machines(SVM) |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
|
