首页 | 本学科首页   官方微博 | 高级检索  
     

二维共轭正交偏最小二乘分析及图像识别应用
引用本文:杨茂龙,孙权森,夏德深.二维共轭正交偏最小二乘分析及图像识别应用[J].计算机工程与应用,2008,44(29):36-39.
作者姓名:杨茂龙  孙权森  夏德深
作者单位:1. 南京国际关系学院,南京,210031;南京理工大学,计算机学院,南京,210094
2. 南京理工大学,计算机学院,南京,210094
摘    要:偏最小二乘(PLS)是一种有效的图像特征抽取方法。不同于其他的多元数据分析方法,PLS综合了PCA与CCA的优点,抽取对样本具有最佳解释能力的成分。讨论了偏最小二乘法建模思想及非迭代算法、共轭正交算法和基于2D特征抽取时的算法原理和特点,以及PLS用于图像识别时类隶属矩阵的构造。在ORL与Yale人脸库上的实验结果表明用2DCOPLS抽取的特征进行图像识别的效果更好,更稳定。

关 键 词:偏最小二乘  非迭代偏最小二乘  共轭正交  二维特征提取  图像识别
收稿时间:2008-5-27
修稿时间:2008-6-23  

Conjugate orthonormalized partial least squares regression and its application in image recognition
YANG Mao-long,SUN Quan-sen,XIA De-shen.Conjugate orthonormalized partial least squares regression and its application in image recognition[J].Computer Engineering and Applications,2008,44(29):36-39.
Authors:YANG Mao-long  SUN Quan-sen  XIA De-shen
Affiliation:1.International Studies University,Nanjing 210031,China 2.Department of Computer Science,Nanjing University of Science &; Technology,Nanjing 210094,China
Abstract:It is an effective approach for image feature extraction by Partial Least Squares(PLS) regression method.The good qualities of PCA and CCA in feature extraction are combined in PLS,which can extract the components interpreting the samples optimally.The theories of feature extracting by PLS,non-iterative PLS and orthonormalized PLS are discussed,and the class membership matrix of 1D and 2D is constructed in image recognition,too.The experiment results on ORL and Yale face image database have shown that the extracted feature by 2DCOPLS can achieve good performance in image recognition.
Keywords:Partial Least Squares(PLS)  Non-iterative PLS(NIPLS)  Conjugate Orthonormalized PLS(COPLS)  2D Feature extraction  image recognition
本文献已被 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
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号