Local binary image coding for face image representation is established as a successful
methodology mostly popularized by the well-known local binary pattern operator (LBP) and …

Face recognition subject to uncontrolled imaging conditions still remains a challenge. This
paper proposes a number of counteracts to partly neutralize the adverse effects of the …

This paper addresses face verification in unconstrained settings. For this purpose, first, a
nonlinear binary class-specific kernel discriminant analysis classifier (CS-KDA) based on …

In this paper, we propose a simultaneous local binary feature learning and encoding
(SLBFLE) approach for both homogeneous and heterogeneous face recognition. Unlike …

The evaluation of face recognition algorithms relies on the diversity of the challenges
simulated on the adopted benchmarks. The main face recognition challenges cover the …

In this paper, we propose a context-aware local binary feature learning (CA-LBFL) method
for face recognition. Unlike existing learning-based local face descriptors such as …

This work suggests the 2 LBP variants so-called Neighborhood Difference LBP (ND-LBP)
and Neighborhood Mean LBP (NM-LBP). In ND-LBP, the comparison is conducted among …

This paper presents a compact and efficient yet powerful binary framework based on image
gradients for robust facial representation. It is termed as Binary Gradient Patterns (BGP). To …

Face recognition is still a very demanding area of research. This problem becomes more
challenging in unconstrained environment and in the presence of several variations like …

Face recognition subject to uncontrolled illumination and blur is challenging. Interestingly,
image degradation caused by blurring, often present in real-world imagery, has mostly been …