title: Face verification using local binary pattern-unconstrained minimum average correlation energy correlation filters.
abstract: In this paper, we present a novel approach for face verification using local                 binary pattern (LBP) operators and optical correlation filters. Due to selected                 filter type and LBP method, different performances would have been expected. We let                 LBP operate on training images to form local binary pattern-unconstrained                 minimum average correlation energy (LBP-UMACE) filters as an optical correlation                 filter to enhance recognition rates and reduce error rates simultaneously. As a                 result, we demonstrate that the designed filters have better performance compared                 with UMACE filters. Moreover, the proposed filters are easy to implement and can be                 used in fast and reliable face verification systems.
authors.affiliation: Department of Electrical and Computer Engineering, Semnan University, Semnan, Iran.
authors.forename: Mohammadreza
authors.initials: M
authors.lastname: Maddah
authors.forename: Saeed
authors.initials: S
authors.lastname: Mozaffari