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G. Hermosilla, J. R. del Solar, R. Verschae, M. Correa, “A comparative study of thermal face recognition methods in unconstrained environments,” Pattern Recognition 45 (2012) 2445-2459.

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Article

Illumination-Invariant Face Recognition in Hyperspectral Images

1Computer Vision Laboratory, Department of Electrical Engineering and Computer Science, University of California, Irvine, USA


Journal of Computer Sciences and Applications. 2019, Vol. 7 No. 1, 21-30
DOI: 10.12691/jcsa-7-1-4
Copyright © 2019 Science and Education Publishing

Cite this paper:
Han Wang, Glenn Healey. Illumination-Invariant Face Recognition in Hyperspectral Images. Journal of Computer Sciences and Applications. 2019; 7(1):21-30. doi: 10.12691/jcsa-7-1-4.

Correspondence to: Han  Wang, Computer Vision Laboratory, Department of Electrical Engineering and Computer Science, University of California, Irvine, USA. Email: wanghan1207@gmail.com

Abstract

Illumination-invariant face recognition remains a challenging problem. Previous studies use either spatial or spectral information to address this problem. In this paper, we propose an algorithm that uses spatial and spectral information simultaneously. We first learn a basis in the spectral domain. We then extract spatial features using 2D Gabor filters. Finally, we use the basis and the spatial features to classify face images. We demonstrate the effectiveness of the algorithm on a database of 200 subjects.

Keywords