A Method for Robust Multispectral Face Recognition

  • Francesco Nicolo
  • Natalia A. Schmid
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6754)


Matching Short Wave InfraRed (SWIR) face images against a face gallery of color images is a very challenging task. The photometric properties of images in these two spectral bands are highly distinct. This work presents a new cross-spectral face recognition method that encodes both magnitude and phase of responses of a classic bank of Gabor filters applied to multi-spectral face images. Three local operators: Simplified Weber Local Descriptor, Local Binary Pattern, and Generalized Local Binary Pattern are involved. The comparison of encoded face images is performed using the symmetric Kullbuck-Leibler divergence. We show that the proposed method provides high recognition rates at different spectra (visible, Near InfraRed and SWIR). In terms of recognition rates it outperforms Faceit®G8, a commercial software distributed by L1.


Face recognition SWIR Gabor wavelets Simplified Weber Local Descriptor Local Binary Pattern Generalized Local Binary Pattern Kullback Leibler divergence 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Francesco Nicolo
    • 1
  • Natalia A. Schmid
    • 1
  1. 1.Department of CSEEWest Virginia UniversityMorgantownUSA

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