| 改进的2DPCA人脸识别算法 |
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| 引用本文： | 伍行素,余为益.改进的2DPCA人脸识别算法[J].计算机系统应用,2011,20(6):212-215. |
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| 作者姓名： | 伍行素 余为益 |
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| 作者单位： | 上饶师范学院数学与计算机科学学院,上饶,334001 |
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| 摘 要： | 在对2DPCA人脸识别方法研究的基础上,提出一种改进的2DPCA人脸识别算法,该算法对训练集进行两次2DPCA特征提取,以此重建散布矩阵,从而大大降低特征矩阵的存储空间.并在标准Yale与ORL人脸识别数据库上进行对比实验,改进的2DPCA人脸算法能有效改善识别性能,优于传统的2DPCA方法.最后,再通过和PCA,LD...
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| 关 键 词： | 人脸识别 二维主元分析 特征提取 |
| 收稿时间： | 2011/1/31 0:00:00 |
| 修稿时间： | 3/5/2011 12:00:00 AM |
Improved 2DPCA Method for Face Recognition |
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| WU Xing-Su and YU Wei-Yi.Improved 2DPCA Method for Face Recognition[J].Computer Systems& Applications,2011,20(6):212-215. |
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| Authors: | WU Xing-Su and YU Wei-Yi |
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| Affiliation: | WU Xing-Su,YU Wei-Yi (School of Mathematics and Computer Science,ShangRao Normal University,Shangrao 334001,China) |
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| Abstract: | After detail analysis the traditional algorithm of 2DPCA,an improved recognition algorithm whose feature extraction applied twice is presented,it can reduce dimensionality.Extensive experiments are performed on the ORL and Yale face databases.The result shows that the improved algorithm has higher feature speed and recognition accuracy than traditional 2DPCA.Finally,compared with PCA,LDA,LPP,etc.,the proposed algorithm is superior to other algorithms in recognition rate. |
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| Keywords: | face recognition two-dimensional principal component analysis(2DPCA) feature extractio |
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