A comparison of genetic feature selection and weighting techniques for multi-biometric recognition

Authors:
Khary Popplewell;Aniesha Alford;Gerry Dozier;Kelvin Bryant;John Kelly;Josh Adams;Tamirat Abegaz;Kamiliah Purrington;Joseph Shelton
Affiliations:
North Carolina Agricultural and Technical State University, Greensboro, NC;North Carolina Agricultural and Technical State University, Greensboro, NC;North Carolina Agricultural and Technical State University, Greensboro, NC;North Carolina Agricultural and Technical State University, Greensboro, NC;North Carolina Agricultural and Technical State University, Greensboro, NC;North Carolina Agricultural and Technical State University, Greensboro, NC;North Carolina Agricultural and Technical State University, Greensboro, NC;North Carolina Agricultural and Technical State University, Greensboro, NC;North Carolina Agricultural and Technical State University, Greensboro, NC
Venue:
Proceedings of the 49th Annual Southeast Regional Conference
Year:
2011

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Abstract

In this paper, we compare genetic-based feature selection (GEFeS) and weighting (GEFeW) techniques for multi-biometric recognition using face and periocular biometric modalities. Our results show that fusing face and periocular features outperforms face-only and periocular-only biometric recognition. Of the two genetic-based approaches, GEFeW outperforms GEFeS.