Orthogonal moments provide an efficient mathematical framework for computer vision,
image analysis, and pattern recognition. They are derived from the polynomials that are …

Images are one of the most prominently used digital information sharing medium now a
days. Due to availability of state-of-the-art image editing tools it has become very easy to …

An in-depth description of the state-of-the-art of 3D shape analysis techniques and their
applications This book discusses the different topics that come under the title of" 3D shape …

Sparse representation of images using orthogonal two-dimensional Krawtchouk moments
(2D KCMs) for face recognition is motivated by their ability to capture region-based higher …

Vector field images are a type of new multidimensional data that appear in many
engineering areas. Although the vector fields can be visualized as images, they differ from …

Rapid growth in the transfer of multimedia information over the Internet requires algorithms
to retrieve a queried image from large image database repositories. The proposed content …

Invariants to image scaling composed of Gaussian–Hermite moments are introduced in this
paper for the first time. To achieve the invariance, we propose to modulate the Gaussian …

This paper presents a statistical face recognition algorithm by expressing face images in
terms of orthogonal two-dimensional Gaussian-Hermite moments (2D-GHMs). Motivation for …

In recent year, 3D face images play a major role in face recognition over corresponding 2D
images. In this work, the 3D range images are used for face recognition based on region …

The pivotal purpose of this literature is to describe a new approach for 3D faces recognition
in the presence of pose, expression, as well as illumination based on fusion of wavelet …