Open AccessExtraction of significant features using GLDM for Covid-19 prediction
Author(s) -
K. Sushmithawathi,
P. Indra
Publication year - 2022
Publication title -
journal of trends in computer science and smart technology
Language(s) - English
Resource type - Journals
ISSN - 2582-4104
DOI - 10.36548/jtcsst.2021.4.004
Subject(s) - covid-19 , preprocessor , pattern recognition (psychology) , cluster analysis , artificial intelligence , median filter , segmentation , computer science , noise (video) , feature extraction , filter (signal processing) , fuzzy logic , computer vision , mathematics , medicine , image processing , image (mathematics) , disease , pathology , infectious disease (medical specialty)
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, images are pre-processed by filters like Median filter and Noise adaptive fuzzy switching median filter, and then the quality measurements like MSE, and PSNR are calculated. After preprocessing, segmentation is done by K-means and Robust self sparse fuzzy clustering algorithm, and then the parameters like LMSE and NAE are calculated. Finally, to get optimum results, feature extraction using GLDM is performed which helps in identifying whether it's a normal lung disease like pneumonia or the patient is affected by covid.