Face Recognition Based On Gabor Local Feature and Convolutional Neural Network

DOI

10.2991/iccia-17.2017.94How to use a DOI?

Keywords

Gabor features, Convolutional neural network, Face recognition

Abstract

Since the distribution of kernel function of Gabor transform and the Two-Dimensional receptive field profiles of mammalian simple cells in the primary visual cortex is very similar, and has the direction selectivity and good spatial locality, so the acquisition of spatial scale information of multiple directions and local structure features in the local regions of images provide a more effective method. The method is based on the Gabor transform and fused the convolutional neural network of the powerful learning ability. The local features of the Gabor transform is used as the input of the neural network, the neural network is used to classify the samples. In ORL face database, the experimental results show that the face recognition methods based on Gabor local features and convolutional neural network in the same conditions obtain higher face recognition rate and the robustness.

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  - Weimeng Qin
AU  - Lie Wang
AU  - Wen Luo
PY  - 2016/07
DA  - 2016/07
TI  - Face Recognition Based On Gabor Local Feature and Convolutional Neural Network
BT  - Proceedings of the 2nd International Conference on Computer Engineering, Information Science & Application Technology (ICCIA 2017)
PB  - Atlantis Press
SP  - 559
EP  - 564
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccia-17.2017.94
DO  - 10.2991/iccia-17.2017.94
ID  - Qin2016/07
ER  -