DocumentCode :
179364
Title :
Research for Face Recognition Based on Gabor Wavelet and Sparse Representation
Author :
Xiaohong Hu
Author_Institution :
Coll. of Comput. Sci. & Technol., Beihua Univ., Jilin, China
fYear :
2014
fDate :
15-16 June 2014
Firstpage :
764
Lastpage :
767
Abstract :
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.
Keywords :
face recognition; feature extraction; image representation; wavelet transforms; Gabor wavelet transformation; face image; face recognition; facial features; over-complete dictionary; sparse facial feature; sparse representation algorithm; structure information; training image set; Face; Face recognition; Facial features; Feature extraction; Training; Vectors; Wavelet transforms; Face recognition; Feature extraction; Gabor wavelet; Sparse representation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Systems Design and Engineering Applications (ISDEA), 2014 Fifth International Conference on
Conference_Location :
Hunan
Print_ISBN :
978-1-4799-4262-6
Type :
conf
DOI :
10.1109/ISDEA.2014.173
Filename :
6977708
Link To Document :
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