DocumentCode :
1395909
Title :
Fusing Local Patterns of Gabor Magnitude and Phase for Face Recognition
Author :
Xie, Shufu ; Shan, Shiguang ; Chen, Xilin ; Chen, Jie
Author_Institution :
Key Lab. of Intell. Inf. Process., Chinese Acad. Sci. (CAS), Beijing, China
Volume :
19
Issue :
5
fYear :
2010
fDate :
5/1/2010 12:00:00 AM
Firstpage :
1349
Lastpage :
1361
Abstract :
Gabor features have been known to be effective for face recognition. However, only a few approaches utilize phase feature and they usually perform worse than those using magnitude feature. To investigate the potential of Gabor phase and its fusion with magnitude for face recognition, in this paper, we first propose local Gabor XOR patterns (LGXP), which encodes the Gabor phase by using the local XOR pattern (LXP) operator. Then, we introduce block-based Fisher´s linear discriminant (BFLD) to reduce the dimensionality of the proposed descriptor and at the same time enhance its discriminative power. Finally, by using BFLD, we fuse local patterns of Gabor magnitude and phase for face recognition. We evaluate our approach on FERET and FRGC 2.0 databases. In particular, we perform comparative experimental studies of different local Gabor patterns. We also make a detailed comparison of their combinations with BFLD, as well as the fusion of different descriptors by using BFLD. Extensive experimental results verify the effectiveness of our LGXP descriptor and also show that our fusion approach outperforms most of the state-of-the-art approaches.
Keywords :
Gabor filters; face recognition; feature extraction; image fusion; Gabor magnitude; block-based Fisher linear discriminant; face recognition; local Gabor XOR patterns; local pattern fusion; Face representation; Fisher´s linear discriminant (FLD); fusion; histogram; local Gabor XOR patterns (LGXP); Algorithms; Biometry; Face; Image Enhancement; Image Interpretation, Computer-Assisted; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Subtraction Technique;
fLanguage :
English
Journal_Title :
Image Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1057-7149
Type :
jour
DOI :
10.1109/TIP.2010.2041397
Filename :
5398909
Link To Document :
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