Fusion of LBP and SWLD using spatio-spectral information for hyperspectral face recognition

Zhihua Xie; Peng Jiang; Shuai Zhang; Jinquan Xiong

doi:10.1117/12.2291611

12 January 2018 Fusion of LBP and SWLD using spatio-spectral information for hyperspectral face recognition

Zhihua Xie, Peng Jiang, Shuai Zhang, Jinquan Xiong

Proceedings Volume 10620, 2017 International Conference on Optical Instruments and Technology: Optoelectronic Imaging/Spectroscopy and Signal Processing Technology; 1062016 (2018) https://doi.org/10.1117/12.2291611
Event: International Conference on Optical Instruments and Technology 2017, 2017, Beijing, China

Abstract

Hyperspectral imaging, recording intrinsic spectral information of the skin cross different spectral bands, become an important issue for robust face recognition. However, the main challenges for hyperspectral face recognition are high data dimensionality, low signal to noise ratio and inter band misalignment. In this paper, hyperspectral face recognition based on LBP (Local binary pattern) and SWLD (Simplified Weber local descriptor) is proposed to extract discriminative local features from spatio-spectral fusion information. Firstly, the spatio-spectral fusion strategy based on statistical information is used to attain discriminative features of hyperspectral face images. Secondly, LBP is applied to extract the orientation of the fusion face edges. Thirdly, SWLD is proposed to encode the intensity information in hyperspectral images. Finally, we adopt a symmetric Kullback-Leibler distance to compute the encoded face images. The hyperspectral face recognition is tested on Hong Kong Polytechnic University Hyperspectral Face database (PolyUHSFD). Experimental results show that the proposed method has higher recognition rate (92.8%) than the state of the art hyperspectral face recognition algorithms.

Citation Download Citation

Zhihua Xie, Peng Jiang, Shuai Zhang, and Jinquan Xiong "Fusion of LBP and SWLD using spatio-spectral information for hyperspectral face recognition", Proc. SPIE 10620, 2017 International Conference on Optical Instruments and Technology: Optoelectronic Imaging/Spectroscopy and Signal Processing Technology, 1062016 (12 January 2018); https://doi.org/10.1117/12.2291611

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