本文已被：浏览 1610次 下载 3561次
Received:January 31, 2011 Revised:March 05, 2011
Received:January 31, 2011 Revised:March 05, 2011
中文摘要: 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.
文章编号： 中图分类号： 文献标志码：
基金项目:
引用文本：
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
WU Xing-Su,YU Wei-Yi.Improved 2DPCA Method for Face Recognition.COMPUTER SYSTEMS APPLICATIONS,2011,20(6):212-215
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
WU Xing-Su,YU Wei-Yi.Improved 2DPCA Method for Face Recognition.COMPUTER SYSTEMS APPLICATIONS,2011,20(6):212-215
