Gender classification aims at recognizing a person's gender. Despite the high accuracy
achieved by state-of-the-art methods for this task, there is still room for improvement in …

Image texture description and analysis technology are the basis of many practical
applications in pattern recognition. This paper presents a novel and simple, yet powerful …

In this paper, we propose a palm vein recognition system that combines two approaches
using a decision-level fusion strategy. The first approach employs Binarized Statistical …

Automatic assessing the quality of an image is a critical problem for a wide range of
applications in the fields of computer vision and image processing. For example, many …

Motivated by researching new image texture modeling that improves state-of-the-art LBP
variants and non-LBP descriptors, this paper proposes a novel approach for constructing …

This paper presents new modeling of local binary patterns for texture representation.
Referred to as local binary gradient contours (LBGC), the proposed models are expected to …

There are many image classification methods, but it remains unclear which methods are
most helpful for analyzing and intelligently identifying ophthalmic images. We select …

Pattern recognition and computer vision fields experienced the proposal of several
architectures and approaches to deal with the demands of real world applications including …

Local binary pattern (LBP) is one of the most successful feature descriptors. However, LBP
and its variants have not been as successful as other feature descriptors in video anomaly …

Human gender is one of the important demographic distinctiveness for facial image
description. In this paper, a novel method is proposed for gender classification from real …