The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XL-5/W6
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-5/W6, 59–63, 2015
https://doi.org/10.5194/isprsarchives-XL-5-W6-59-2015
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-5/W6, 59–63, 2015
https://doi.org/10.5194/isprsarchives-XL-5-W6-59-2015

  18 May 2015

18 May 2015

FACE RECOGNITION USING LOCAL QUANTIZED PATTERNS AND GABOR FILTERS

V. Khryashchev1, A. Priorov1, O. Stepanova1, and A. Nikitin2 V. Khryashchev et al.
  • 1P.G. Demidov Yaroslavl State University, Yaroslavl, Russia
  • 2PicLab LLC, Yaroslavl, Russia

Keywords: Face Recognition, Eye Center Localization, Local Quantized Patterns, Gabor Filters, Histogram Comparing

Abstract. The problem of face recognition in a natural or artificial environment has received a great deal of researchers’ attention over the last few years. A lot of methods for accurate face recognition have been proposed. Nevertheless, these methods often fail to accurately recognize the person in difficult scenarios, e.g. low resolution, low contrast, pose variations, etc. We therefore propose an approach for accurate and robust face recognition by using local quantized patterns and Gabor filters. The estimation of the eye centers is used as a preprocessing stage. The evaluation of our algorithm on different samples from a standardized FERET database shows that our method is invariant to the general variations of lighting, expression, occlusion and aging. The proposed approach allows about 20% correct recognition accuracy increase compared with the known face recognition algorithms from the OpenCV library. The additional use of Gabor filters can significantly improve the robustness to changes in lighting conditions.