Developed Histogram of Oriented Gradients-based Feature Extraction for Covid-19 X-Ray Image Classification

Identification of Covid-19 use X-ray images to diagnose the level of the covid-19 diseases. The patients can be misdiagnosed due to the similarity between the radiographic images of Covid-19 and pneumonia. Therefore, this research aims to develop automatic screening systems to classify the xray images effectively. Developed Histogram of Oriented Gradients (HOG) algorithm is proposed to be used for features extraction step. The algorithm is developed by enlarging the matrix of extracted features as input to the classification step. The classification step employed three classification algorithms, namely Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Decision Tree (DT) to classify the image based on the proposed features. The study revealed that the developed HOG algorithm as features extraction method and Medium Gaussian SVM yielded the maximum performance values of 98.28% for accuracy, 97.56% for precision, 97.56% for recall, 98.67% for specificity, and 97.56% for F-score.