Proceedings of the 2016 International Conference on Artificial Intelligence: Technologies and Applications

Research of Face Recognition Method Use of MRA-Framework

Authors
Zhaoying Wu, Feng Ma, Wanshe Li
Corresponding Author
Zhaoying Wu
Available Online January 2016.
DOI
https://doi.org/10.2991/icaita-16.2016.1How to use a DOI?
Keywords
face recognition; MRA-framelet; principal component analysis (PCA); wavelet transformation; noise adding
Abstract
Of the face image after adding noise, face recognition rate of traditional PCA method will be significantly lowered, this paper will use orthogonal wavelet + PCA and wavelet frame + PCA methods to study it respectively. First, the face image processing plus noise, then decomposition the image under the use of orthogonal wavelet and wavelet frame, and then sub-graph of decomposition will be dimensionality reduction and feature extraction using the methods of PCA, and finally, use third-order nearest neighbor classifier for classification and identification. And on the ORL face database, the experiment results show the effectiveness of this method, good way to improve the recognition rate plus noise situation servants face image.
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This is an open access article distributed under the CC BY-NC license.

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Volume Title
Proceedings of the 2016 International Conference on Artificial Intelligence: Technologies and Applications
Series
Advances in Intelligent Systems Research
Publication Date
January 2016
ISBN
978-94-6252-162-9
ISSN
1951-6851
DOI
https://doi.org/10.2991/icaita-16.2016.1How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Zhaoying Wu
AU  - Feng Ma
AU  - Wanshe Li
PY  - 2016/01
DA  - 2016/01
TI  - Research of Face Recognition Method Use of MRA-Framework
BT  - Proceedings of the 2016 International Conference on Artificial Intelligence: Technologies and Applications
PB  - Atlantis Press
SP  - 1
EP  - 5
SN  - 1951-6851
UR  - https://doi.org/10.2991/icaita-16.2016.1
DO  - https://doi.org/10.2991/icaita-16.2016.1
ID  - Wu2016/01
ER  -