Research for face recognition based on Gabor wavelet and sparse representation

被引：0

作者：

Hu, Xiaohong ^{[1
]}

机构：

[1] Beihua Univ, Coll Comp Sci & Technol, Fengman 132021, Jilin, Peoples R China

来源：

2014 Fifth International Conference on Intelligent Systems Design and Engineering Applications (ISDEA) | 2014年

关键词：

Sparse representation; Gabor wavelet; Face recognition; Feature extraction;

D O I：

10.1109/ISDEA.2014.173

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

On the basis of research for sparse representation and Gabor wavelet, a new method for face recognition combined Gabor with representation is proposed in this paper. Gabor wavelet transformation is used for face image from the training image set to obtain facial features, the over-complete dictionary is built by the Gabor features from all training set, and the sparse facial feature is obtained by sparse representation algorithm. Finally, the classifier based on fusion is designed for face recognition. The experimental results show that the improved method can extract facial features and structure information more effectively, and it also can improve face recognition rate greatly.

引用

页码：764 / 767

页数：4