NDLI: Face recognition using Histogram of co-occurrence Gabor phase patterns

Content Provider	IEEE Xplore Digital Library
Author	Cong Wang Zhenhua Chai Zhenan Sun
Copyright Year	2013
Description	Author affiliation: Center for Res. on Intell. Perception & Comput. (CRIPAC), Inst. of Autom., Beijing, China (Cong Wang; Zhenhua Chai; Zhenan Sun)
Abstract	The fusion of Local Binary Patterns (LBP) and Gabor magnitude features has been demonstrated to be one of the most successful descriptors for face recognition. Recently, several Gabor phase based features like Histogram of Gabor Phase Patterns (HGPP) and Local Gabor XOR Patterns (LGXP) also show competitive results and complementary attributes to Gabor magnitude based features. However, in these two typical Gabor phase based approaches only the binary relationship between neighboring Gabor phases is used, which may lose some discriminative information. To investigate the potential of Gabor phase features for robust face recognition, this paper proposes a novel local descriptor, named Histogram of Co-occurrence Gabor Phase Patterns (HCGPP). In HCGPP, Gabor Phase features are first extracted and quantized into different ranges. Second we estimate the histograms of cooccurrence Gabor phase patterns in each face region. Finally, a nearest-neighbor classifier with the dissimilarity measure $χ^{2}$ is used for classification. Extensive experimental results on FERET and AR databases show the significant advantages of the proposed method over the state-of-the art ones in terms of recognition rate.
Starting Page	2777
Ending Page	2781
File Size	406663
Page Count	5
File Format	PDF
ISBN	9781479923410
DOI	10.1109/ICIP.2013.6738572
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-09-15
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	HCGPP Face recognition feature extraction local descriptor Gabor phase
Content Type	Text
Resource Type	Article

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