DocumentCode :
2425081
Title :
A novel face description by local multi-channel Gabor histogram sequence binary pattern
Author :
Gao, Tao ; He, Mingyi
Author_Institution :
Sch. of Electron. & Inf., Northwestern Polytech. Univ., Xi´´an
fYear :
2008
fDate :
7-9 July 2008
Firstpage :
1240
Lastpage :
1244
Abstract :
A novel method for face description by local multi-channel Gabor histogram sequence binary pattern (M-LGHSBP) is proposed. The motivation for the M-LGHSBP model is to find more rich and canonical texture measurement and deal with the high dimension problem of the local Gabor feature vector. Firstly, the normalized face image is sampled and blocked. Secondly, the blocked image is filtered by multi-orientation Gabor filters with multi-scale, which acquires rich and canonical texture measurement. Thirdly, the multi-degree LBP is used to solve the high dimension problem of local Gabor feature and its output can express both local and global features. Finally, ICA and RBF are adopted to extract feature and class. Experimental results on ORL and YEL face database show that the proposed algorithm, which achieves recognition accuracy of above 98%, is more effective than the well known face recognition algorithms, including PCA, ICA, Gabor, Local Gabor, LBP and Gabor-ICA.
Keywords :
Gabor filters; face recognition; feature extraction; image classification; image sampling; image sequences; image texture; independent component analysis; blocked image filtering; canonical texture measurement; face description; feature extraction; image classification; image sampling; independent component analysis; local Gabor feature vector; local multichannel Gabor histogram sequence binary pattern; multi orientation Gabor filter; Data mining; Face detection; Face recognition; Feature extraction; Frequency; Gabor filters; Histograms; Independent component analysis; Principal component analysis; Robustness;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Audio, Language and Image Processing, 2008. ICALIP 2008. International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-1723-0
Electronic_ISBN :
978-1-4244-1724-7
Type :
conf
DOI :
10.1109/ICALIP.2008.4590128
Filename :
4590128
Link To Document :
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