Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-5/W6, 59-63, 2015
http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-5-W6/59/2015/
doi:10.5194/isprsarchives-XL-5-W6-59-2015
© Author(s) 2015. This work is distributed
under the Creative Commons Attribution 3.0 License.
 
18 May 2015
FACE RECOGNITION USING LOCAL QUANTIZED PATTERNS AND GABOR FILTERS
V. Khryashchev1, A. Priorov1, O. Stepanova1, and A. Nikitin2 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.
Conference paper (PDF, 922 KB)


Citation: Khryashchev, V., Priorov, A., Stepanova, O., and Nikitin, A.: FACE RECOGNITION USING LOCAL QUANTIZED PATTERNS AND GABOR FILTERS, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-5/W6, 59-63, doi:10.5194/isprsarchives-XL-5-W6-59-2015, 2015.

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