Investigation of image classification using hog, glcm features, and svm classifier

Abstract

Recently, in order to solve the problem of image classification, some image features and classifiers play more and more important role in the related research field. This article investigates an image classification method by the histogram of oriented gradient (HOG) features, the gray-level co-occurrence matrix (GLCM) features, and the support vector machine (SVM) classifier. By obtaining the HOG and the GLCM features of image, the combination of them is inputted into the SVM for the training and the test. The experiment results have manifested the effectiveness of the proposed method. The use of the combination of HOG features and GLCM features in image classification is far superior to the use of them alone.