Different Age Face Recognition Techniques based on LBP and SVM Algorithm

DOI

10.2991/ammee-17.2017.57How to use a DOI?

Keywords

face feature, support vector machine, principal component analysis, ROC

Abstract

In view of the different styles of pictures, we first on the selected picture library for noise reduction, filtering and wrinkle and other treatment, so that the picture library to meet the requirements of the title, while reducing the impact of age factors on identification, simplified model calculation. In order to further improve the recognition rate of the system, this paper improves the facial feature extraction and the design of the classifier. The LBP algorithm is used to extract the microscopic spatial structure of the face region, and the SDM algorithm is used to locate the face The CSLBP operator extracts the neighborhood characteristics of each feature point. As the image pixel density is too large, we use the main component analysis method (PCA) for dimension reduction processing. Finally, the data into SVM and other classifiers for algorithm learning, comprehensive comparison, select the best effect of the classifier as a final training model method.

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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TY  - CONF
AU  - Meng Xu
AU  - Mingjie Wu
AU  - Xin Su
PY  - 2017/06
DA  - 2017/06
TI  - Different Age Face Recognition Techniques based on LBP and SVM Algorithm
BT  - Proceedings of the Advances in Materials, Machinery, Electrical Engineering (AMMEE 2017)
PB  - Atlantis Press
SP  - 289
EP  - 297
SN  - 2352-5401
UR  - https://doi.org/10.2991/ammee-17.2017.57
DO  - 10.2991/ammee-17.2017.57
ID  - Xu2017/06
ER  -