NDLI: Research of face recognition based on SVD

Content Provider	IEEE Xplore Digital Library
Author	Song Hai-zhou Qian Ying
Copyright Year	2009
Description	Author affiliation: The Research Centre of Medical Image and Information System, College of Computer and Science Technology, Chongqing University of Posts and Telecommunications, China (Song Hai-zhou; Qian Ying)
Abstract	Through the analysis of the singular value vector and left-right orthogonal Characteristic Matrix, this paper affirms that the singular vectors from imaging matrix decomposition can show image gray, which is related to gray distribution density; the Maximum component of the singular vectors presents the position of image levels, and other components of the singular vectors show the width of image levers. Moreover, combination the maximum singular value and the other components of the singular vectors are exactly able to ascertain image gray. The decomposed left-right orthogonal Characteristic Matrix can show structure information of picture contour. Finally, a kind of recognition algorithm based on basis space is brought forward, emulated in the ORL and ORL_IC database. The conclusion affirms the validity of the analysis.
Starting Page	255
Ending Page	259
File Size	2141882
Page Count	5
File Format	PDF
ISBN	9781424439874
DOI	10.1109/IASP.2009.5054626
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-04-11
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image recognition Face recognition Eigenvector Educational institutions Matrix decomposition Distributed computing Information analysis Information systems Image analysis Image databases Basis Space Characteristic Matrix Biomedical imaging singular value decomposition (SVD)
Content Type	Text
Resource Type	Article

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