Proceedings of the 2017 2nd Joint International Information Technology, Mechanical and Electronic Engineering Conference (JIMEC 2017)

A New Face Recognition Method Based On SVD

Authors
Yuanyuan Ma, Dengyin Zhang
Corresponding Author
Yuanyuan Ma
Available Online October 2017.
DOI
10.2991/jimec-17.2017.64How to use a DOI?
Keywords
face recognition; singular value decomposition; singular value vector; matrix similarity
Abstract

In order to further improve the accuracy of face recognition and reduce the time complexity, this paper presents a new method of face recognition based on the singular value decomposition (SVD). Combining the characteristics of singular value vector (SVV) and orthogonal matrix similarity, a new criterion is established to obtain the decision category of the face to be tested. The ORL face database is used to verify the recognition effect of the proposed method. Experiment results show that the proposed method is superior to other methods in recognition rate and time complexity.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2017 2nd Joint International Information Technology, Mechanical and Electronic Engineering Conference (JIMEC 2017)
Series
Advances in Computer Science Research
Publication Date
October 2017
ISBN
10.2991/jimec-17.2017.64
ISSN
2352-538X
DOI
10.2991/jimec-17.2017.64How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Yuanyuan Ma
AU  - Dengyin Zhang
PY  - 2017/10
DA  - 2017/10
TI  - A New Face Recognition Method Based On SVD
BT  - Proceedings of the 2017 2nd Joint International Information Technology, Mechanical and Electronic Engineering Conference (JIMEC 2017)
PB  - Atlantis Press
SP  - 291
EP  - 294
SN  - 2352-538X
UR  - https://doi.org/10.2991/jimec-17.2017.64
DO  - 10.2991/jimec-17.2017.64
ID  - Ma2017/10
ER  -