This work proposes a novel face recognition method based on Zernike moments (ZMs) and
Hermite kernels (HKs) to cope with variations in facial expression, changes in head pose …

This study proposes a novel near infrared face recognition algorithm based on a
combination of both local and global features. In this method local features are extracted …

Face recognition is a rapidly growing research area, which is based heavily on the methods
of machine learning, computer vision, and image processing. We propose a rotation and …

This paper presents a robust two-stage face recognition approach that combines the traits of
global features in first stage and the local features in second stage. The global features are …

This paper presents an approach to boost the performance of pseudo Zernike moments in
face recognition. This approach is a hybrid of a kernel trick, discriminant function and …

The face recognition under the uncontrolled conditions is a widely debated research topic
since from last decade due to technology advancement and the emergence of face …

This paper presents a simple but effective method for face recognition, named nearest
orthogonal matrix representation (NOMR). Specifically, the specific individual subspace of …

Abstract Face recognition with Kernel Sparse Representation based Classification (KSRC)
has shown its great classification performance, and as an extension of Sparse …

Feature extraction is one of the important tasks in face recognition. Moments are widely used
feature extractor due to their superior discriminatory power and geometrical invariance …

In face recognition tasks, one kind of feature set is not adequate to generate superior results;
thus, selection and combination of complementary features are crucial steps. In this paper …