Genetic based LBP feature extraction and selection for facial recognition

Authors:
Joseph Shelton;Gerry Dozier;Kelvin Bryant;Joshua Adams;Khary Popplewell;Tamirat Abegaz;Kamilah Purrington;Damon L. Woodard;Karl Ricanek
Affiliations:
North Carolina Agricultural and Technical State University, NC;North Carolina Agricultural and Technical State University, NC;North Carolina Agricultural and Technical State University, NC;North Carolina Agricultural and Technical State University, NC;North Carolina Agricultural and Technical State University, NC;North Carolina Agricultural and Technical State University, NC;North Carolina Agricultural and Technical State University, NC;Clemson University, Clemson, S.C.;University of North Carolina at Wilmington, CIS Building, Wilmington NC
Venue:
Proceedings of the 49th Annual Southeast Regional Conference
Year:
2011

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Abstract

This paper presents a novel approach to LBP feature extraction. Unlike other LBP feature extraction methods, we evolve the number, position, and the size of the areas of feature extraction. The approach described in this paper also attempts to minimize the number of areas as well as the size in an effort to reduce the total number of features needed for LBP-based face recognition. In addition to reducing the number of features by 63%, our approach also increases recognition accuracy from an average of 99.04% to 99.84%.