改进的2DPCA 人脸识别算法
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Improved 2DPCA Method for Face Recognition
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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,LDA,LPP 等其他非2DPCA 经典算法进行对比仿真实验,验证了本文算法的高有效性。

    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.

    参考文献
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伍行素,余为益.改进的2DPCA 人脸识别算法.计算机系统应用,2011,20(6):212-215

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  • 收稿日期:2011-01-31
  • 最后修改日期:2011-03-05
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