find similarity percentage for two binary images in matlab

To find the similarity percentage between two binary images in MATLAB, you can use the Structural Similarity (SSIM) index. The SSIM index is a metric that compares two images based on their structural information, luminance, and contrast. It returns a value between 0 and 1, where higher values indicate higher similarity between the images.

Here is an example code snippet that shows how to calculate the SSIM index between two binary images:

main.m
% Read the images
img1 = imread('binary_image_1.png');
img2 = imread('binary_image_2.png');

% Convert the images to double precision
img1 = im2double(img1);
img2 = im2double(img2);

% Calculate the SSIM index
ssim_val = ssim(img1, img2);

% Display the similarity percentage
similarity_perc = ssim_val * 100;
disp(['Similarity percentage: ' num2str(similarity_perc) '%']);
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In this example, the imread function is used to read the two binary images. The im2double function is used to convert the images to double precision. The ssim function is then used to calculate the SSIM index between the images. Finally, the similarity percentage is calculated by multiplying the SSIM index by 100 and displayed to the console.