Artificial Intelligence for Sustainable Applications

2Bounding Box Region-Based Segmentation of COVID-19 X-Ray Images by Thresholding and Clustering

Kavitha S.* and Hannah Inbarani

Department of Computer Science, Periyar University, Salem, India

Abstract

Image segmentation is used to decrease the complication of an image for further processing, analysis and visualization. This work presents the Bounding Box-based segmentation methods through thresholding, K-Means, and Fuzzy K-Means clustering to segment the COVID-19 chest x-ray images as it involves simple calculations and fast operation. Bounding box is generated over the image to locate the object of interest on an image. Before applying these methods the images are histogram equalized using CLAHE to improve the quality of a foggy image with the limited increase in the contrast. The results are evaluated using Intersection over Union (IoU) and Mean Pixel Accuracy (MPA) with the segmented and the ground truth image.

Keywords: Contrast limited adaptive histogram equalization (CLAHE), bounding box, thresholding, K-Means clustering, fuzzy k-means, mean pixel accuracy (MPA), Intersection over Union (IoU)

2.1 Introduction

Corona virus (COVID-19) is one of the most abundantly spread viruses in the world affecting more than 200 countries causing an overwhelming epidemic. As the virus is causing more deaths, it has increased pressure on health organizations to save the affected patients. Hence, it is necessary to detect the virus in a patient as early as possible to provide efficient ...