Algorithm 1.

Phases to measure the COVID similarity with other abnormalities

START   INPUT: ECG_Samples   OUTPUT: Similarity score   ECG_Samples: Images from classes   I(x)= COVID samples   Similarity score: estimation of COVID   similarity with other four classes   ECG_samples ← [x,y]   // Preprocessing step   Crop_ECG_samples ← Crop (ECG_samples)   Processed_ECG_samples ←   BackGroudRemoval (Crop_ECG_samples)   Enhanced_ ECG_samples ← Morphological   Operation(Processed_ECG_samples)   Resized_ECG_samples ←   imresize(Enhanced _ECG_samples)   // Similarity Estimation   Dataset ← Path of Resized_ECG_samples   from saved directory   DestinationFolder ← Path to save the   results   filePattern ← fullfile(Dataset,   ‘*.jpg’);   jpegFiles ← dir(filePattern);   for k = 1: length(jpegFiles)      baseFileName ← jpegFiles(k).name;      fullFileName ← fullfile(Dataset,      baseFileName);      ECG_sample[J] ←      imread(fullFileName);      Estimated_Similarity(k) ←   sqrt(sum((I(:) - ECG_sample(:)) .∧ 2));   End   SaveResult() and output Similarity   score   FINISH