SVM and ANN classification using GLCM and HOG features for COVID-19 and Pneumonia detection from Chest X-rays

Abstract

Due to the coronavirus pandemic and the lack of an automatic COVID-19 diagnostic system to relieve congestion in health centers and to support the traceability of this disease, this article exposes the implementation of algorithms for automatic diagnosis of lung diseases such as COVID-19 and Pneumonia from chest X-rays (CXR) through GLCM and HOG features extraction using 6300 patches. Then, selecting the best features and different classifiers such as an Support Vector Machine (SVM) and Artificial Neural Network (ANN) to obtain a system maximum accuracy of 93,73% for SVM.