This document discusses various feature descriptors that can be used for texture image classification. It provides an overview of 8 different feature descriptors that have been proposed in recent research: local binary patterns (LBP), dominant local binary patterns (DLBP), completed local binary patterns (CLBP), Weber local descriptor (WLD), local binary count (LBC), discriminant face descriptor (DFD), local vector quantization pattern (LVQP), and dense micro-block difference (DMD). For each descriptor, it briefly explains the approach and compares the methods. The goal of the descriptors is to effectively capture textural features while addressing challenges like rotation, illumination changes, and noise.