| 基于WT-2DICA与改进Fisher算法的人脸识别 |
| |
| 引用本文： | 甘俊英,李春芝.基于WT-2DICA与改进Fisher算法的人脸识别[J].计算机工程,2008,34(4):212-214. |
| |
| 作者姓名： | 甘俊英 李春芝 |
| |
| 作者单位： | 1. 五邑大学信息学院,江门,529020;北京大学视觉与听觉信息处理国家重点实验室,北京,100871
2. 五邑大学信息学院,江门,529020 |
| |
| 基金项目： | 广东省自然科学基金
,
国家重点实验室基金 |
| |
| 摘 要： | 小波变换与二维独立元分析(WT-2DICA)能有效提取人脸图像的高阶统计信息，但不能很好地识别受污损的人脸图像。改进Fisher算法充分考虑了类别信息，避免了传统Fisher算法造成的小样本问题。该文结合2种算法的优点，融合改进Fisher算法的最佳投影方向与WT-2DICA算法的独立基子空间，获得了融合投影方向。实验结果表明，该融合算法具有较好的分类性能。
|
| 关 键 词： | 改进Fisher算法 小波变换与二维独立元分析 分类器融合 人脸识别 |
| 文章编号： | 1000-3428（2008）04-0212-03 |
| 收稿时间： | 2007-04-10 |
| 修稿时间： | 2007年4月10日 |
Face Recognition Based on WT-2DICA and Improved Fisher Algorithm |
| |
| GAN Junying,LI Chun-zhi.Face Recognition Based on WT-2DICA and Improved Fisher Algorithm[J].Computer Engineering,2008,34(4):212-214. |
| |
| Authors: | GAN Junying LI Chun-zhi |
| |
| Affiliation: | (1. School of Information, Wuyi University, Jiangmen 529020; 2. National Laboratory on Machine Perception, Peking University, Beijing 100871) |
| |
| Abstract: | High-order statistical information can be extracted effectively with Two-dimensional Independent Component Analysis based on Wavelet-transform(WT-2DICA), but the method is not valid in the recognition of the damaged images. Improved Fisher method avoids small samples problem in traditional Fisher method by considering category information. Combined with the advantages of two algorithms, fusion projection direction is obtained, which integrates best projection direction from improved Fisher and independent basis subspace from WT-2DICA. Experimental results show that the fusion method is valid in face recognition. |
| |
| Keywords: | improved Fisher algomitm Wavelet-transform and Two-dimensional Independent Component Analysis(WT-2DICA) classifiers fusion face recognition |
| 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》浏览原始摘要信息 |
|
点击此处可从《计算机工程》下载全文 |
