Extraction of significant features using GLDM for Covid-19 prediction

Although Covid-19 caused by the SARS-COV-2 virus, is a deadliest disease, many people experienced mild symptoms and were recovered soon. In this paper, coronavirus can be easily detected using CT scan images of affected patients. Initially, are pre-processed filters like Median filter Noise adaptive fuzzy switching median filter, then quality measurements MSE, PSNR calculated. After preprocessing, segmentation done K-means Robust self sparse clustering algorithm, parameters LMSE NAE Finally, to get optimum results, feature extraction GLDM performed which helps in identifying whether it's normal lung disease pneumonia or patient covid.