Classification of Covid-19 in Chest X-Ray Image

The entire planet is in danger because of the Covid-19 epidemic. It is now seen by people all around the world as a severe problem in China, as it was previously. It has infected more than 150 million individuals throughout the world and harmed more than 30,60,000 people as of June 1, 2021. Finding answers to questions about covid-19 has turned into a severe burden for the medical field. For the direct diagnosis of COVID-19, chest X-rays are a frequent approach. In this study, the pattern analysis methods are incorporated for the automatic classification of images. LBP, HOG, and Hu Moments are extracted to classify the chest X-Ray images using SVM and Random Forest classifiers. The performance of the proposed model is measured using accuracy. The result shows that method is promising and encouraging.