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Detection of COVID-19 Cases using Histogram of Oriented Gradient (HOG) with Support Vector Machine (SVM) Classifier

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2022
Reda Elbarougy, G.M. Behery, Y.M. Younes, Esmail Aboghrara

Reda Elbarougy, G M Behery, Y M Younes and Esmail Aboghrara. Detection of COVID-19 Cases using Histogram of Oriented Gradient (HOG) with Support Vector Machine (SVM) Classifier. International Journal of Computer Applications 183(52):40-44, February 2022. BibTeX

	author = {Reda Elbarougy and G.M. Behery and Y.M. Younes and Esmail Aboghrara},
	title = {Detection of COVID-19 Cases using Histogram of Oriented Gradient (HOG) with Support Vector Machine (SVM) Classifier},
	journal = {International Journal of Computer Applications},
	issue_date = {February 2022},
	volume = {183},
	number = {52},
	month = {Feb},
	year = {2022},
	issn = {0975-8887},
	pages = {40-44},
	numpages = {5},
	url = {},
	doi = {10.5120/ijca2022921943},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


COVID-19 is now considered the most severe and fatal human illness caused by a novel coronavirus.The coronavirus which is considered to have originated in Wuhan, China spread fast around the world in December 2019 and caused a huge the number of fatalities. The early discovery of COVID-19 out of precise analysis, specifically in circumstances where there are no immediately visible symptoms,could lower the patient's risk of death. The demand for supplemental diagnostic equipment has grown because there are no precise and available toolkits for automation. However, recent studies using radiological imaging techniques have revealed important information for detecting the COVID-19.Combining artificial intelligence and radiological imaging techniques can help improve disease recognition accuracy. A machine learning (ML) strategy for recognizing COVID-19 in chest x-ray images is proposed in this paper.Features were extracted using the histogram-oriented gradient (HOG) from x-ray images. The classification performance of the support vector machine (SVM) classifier used in this study was excellent. The proposed HOG feature technique provided high accuracy reach (96.6%).


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Coronavirus, Histogram-oriented gradient, COVID-19, Chest x-ray, Machine learning, Radiology images