Classification of Texture Images Based on the Histogram of Oriented Gradients Using Support Vector Machines

Abstract

Herein, using supportvector machines, texture images were classified based on the histogram oforiented gradients, from which feature vectors were obtained. In addition, thesuccess rate was examined for the feature vectors with different dimensions andthe minimum length of a feature vector for performing classification wasdetermined to be 288 elements.