| 基于保局投影的离线签名识别 |
| |
| 引用本文： | 戴斯荻,夏利民.基于保局投影的离线签名识别[J].计算机工程与应用,2010,46(1):190-193. |
| |
| 作者姓名： | 戴斯荻 夏利民 |
| |
| 作者单位： | 中南大学 信息科学与工程学院，长沙 410075 |
| |
| 基金项目： | 国家自然科学基金No.79816101~~ |
| |
| 摘 要： | 针对离线签名识别中的特征提取问题，提出了一种基于保局投影的签名识别方法。该方法首先对签名图像进行形状特征、伪动态特征和纹理特征的提取；然后采用保局投影得到更具判别性的特征；最后运用支持向量机进行分类识别。实验表明该方法不但能有效地降低特征空间的维数，而且能使分类准确率得到显著提高。
|
| 关 键 词： | 签名识别 特征提取 保局投影 支持向量机 |
| 收稿时间： | 2009-1-4 |
| 修稿时间： | 2009-3-13
|
Off-line signature recognition based on locality preserving projections |
| |
| DAI Si-di,XIA Li-min.Off-line signature recognition based on locality preserving projections[J].Computer Engineering and Applications,2010,46(1):190-193. |
| |
| Authors: | DAI Si-di XIA Li-min |
| |
| Affiliation: | College of Information Science and Engineering，Central South University，Changsha 410075，China |
| |
| Abstract: | In view of the problems of feature extraction in off-line signature recognition,a new signature recognition based on Locality Preserving Projections(LPP) is proposed.Firstly,the shape features,pseudo dynamic features and texture features have been extracted in feature extraction.Then LPP is used to get more discriminant features and at last support vector machine classifier is used for classification.Experimental result shows that the method can not only reduce the dimension of the feature space but also ad... |
| |
| Keywords: | signature recognition feature extraction locality preserving projections support vector machine |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
| 点击此处可从《计算机工程与应用》浏览原始摘要信息 |
|
点击此处可从《计算机工程与应用》下载全文 |
