Deteksi Tepi pada Citra Rontgen Penyakit COVID-19 Menggunakan Metode Sobel

Muhammad Ghozali, Heni Sumarti


Background: Coronavirus Disease 2019 (COVID-19) discovered at the end of 2019 occasioned by coronavirus 2 (SARS-CoV-2) causing severe acute respiratory syndrome and expanded globally so that World Health Organization (WHO) declare a global pandemic. There was a delay of socialization and delivering information to society about this disease. The doctors did a method to detect COVID-19 by reading the correct X-ray images of patients who affected by a coronavirus.

Methods: With advances in the field of computers in the application of image processing techniques method of this research use application to get better digital image results for COVID-19 X-ray images, so make it easier to analyze the X-ray images. There are 13 samples of X-ray images that are processed through the clean the stage with high-pass filtering, then segmented with thresholding technique in the lung area, then the edge detection method is used to mark the area that makes the image detail.

Results: The result of this detection form the pattern of objects and regions of the spread of coronavirus, then there is a limit on the image looks clear enough, with the Sobel method producing white pixels that are so visible as well.

Conclusions: This study to make a simulation of x-ray thorax COVID-19 and know the region of virus infection using Sobel method with thresholding technique that can see the spread of coronavirus and shown that edge detection use Sobel method as one of diagnosing for COVID-19 disease.


X-ray Image; COVID-19; Segmentation; Edge Detection; Sobel method

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