Delong Zhang1, Min Zhang2 and Yongbo Liu This email address is being protected from spambots. You need JavaScript enabled to view it.3

1School of Electric Automation, Weifang University of Science and Technology, Weifang 262700, P.R. China
2Department of Mechanical and Electronic Engineering, Shandong Management University, Ji’nan 250357, P.R. China
3Department of City Management, Hunan City University, Yiyang, Hunan 413000, P.R. China


 

Received: December 30, 2016
Accepted: October 28, 2018
Publication Date: March 1, 2019

Download Citation: ||https://doi.org/10.6180/jase.201903_22(1).0016  

ABSTRACT


Face recognition based on 2D face images is still challenged by the large change of illumination, pose and expression after more than 10 years’ research and its recognition rate is still far away from satisfaction under the change of the above three factors. Gabor wavelet and support vector machine (SVM) are studied. Gabor wavelet has good biological neurons function, and good adaptive change to illumination. Furthermore, SVM can provide good classification effect. Gabor wavelet and SVM are combined with PCAto improve recognition rate of human face. Besides, we put forward a kind of Gabor wavelet feature extraction method based on three-dimensional human face contour line. Five different types of human face recognition are used to verify the effectiveness of this algorithm. The experiment results show that the proposed scheme has higher recognition rate than several traditional schemes.


Keywords: Three Dimension Face Recognition, Gabor Wavelet, Support Vector Machine, Feature Extraction


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