Mathematical Model for Anisotropic diffusion Filter and GLRLM Feature Extraction to Detect Covid-19 from Chest X-Ray Images

In December 2019, the SARS-CoV-2 virus, often referred to as COVID-19, was discovered in Wuhan, China. It is very virulent and has spread very quickly throughout the world. With COVID-19, people have described a wide variety of symptoms, from little discomfort to life-threatening respiratory illness. In this study, chest X-ray scan images are preprocessed using an anisotropic diffusion filter and three classifiers, and the Covid-19 cases are classified from the chest X-ray images using the GLRLM feature extraction approach. Common metrics like sensitivity, selectivity, and accuracy are utilized to compare the performance of the classifiers. When compared to other classifiers in this study, the Gaussian Mixture Model had the best accuracy of 91.07%.