Texture image classification is an active research topic in computer vision that play an
important role in many applications such as visual inspection systems, object tracking …

Local binary pattern is one of the most known descriptors, which is used for texture
classification. Although completed local binary pattern is seemingly the most precise variant …

The sea-land segmentation for optical remote sensing images (RSIs) has a valuable role in
water resources and coastal zones management. However, it is challenging because optical …

An accurate cultural insect detection and recognition relies mainly on a proper automatic
segmentation. This paper deals with butterfly segmentation in ecological images …

High computational burden and low accuracy in non-uniform textures are the two main
challenges of coral reef classification frameworks. To overcome these drawbacks, two novel …

Abstract Local Binary Pattern (LBP) is one of the best descriptors of texture images;
however, it elicits information from the pixels' value over each locality and therefore its value …

Vision-based human activity recognition (HAR) plays a significant role in various practical
demands. Recently, different solutions have been proposed and their performance is …

In this article, a semisupervised weighting method for feature dimension based on entropy is
proposed for classification, dimension reduction, and correlation analysis. For real-world …

In this paper, four novel, simple and robust approaches, which are left to right local binary
patterns (LBPL L2R), top to down local binary patterns (LBP T2D), cube surface local binary …

Butterflies have a prominent role in the agro-ecological ecosystems. Some butterfly
populations can injure wildlife, vegetation, and even humans in addition to causing harm to …