Counting coins on a greyscale image — using morphological and/or f transforms

I am trying to convert the image into a binary image, using the function form: function C = coins2bw(A) where A is a 2D grayscale image variable and C is a 2D binary image variable. The output image C should show the coins as filled in round disks with no other arifacts or stray foreground pixels(background in black while the coins are white). Using only morphological or fourier transforms.

NOTE:-

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I = imread('image.png');
I = imadjust(I);
[centers,radii] = imfindcircles(I,[15 75],'ObjectPolarity','dark','Sensitivity',0.85);
BW = false(size(I,1),size(I,2));
[Xgrid,Ygrid] = meshgrid(1:size(BW,2),1:size(BW,1));
for n = 1:size(centers,1)
BW = BW | (hypot(Xgrid-centers(n,1),Ygrid-centers(n,2)) <= radii(n));
end
maskedImage = I;
maskedImage(~BW) = 0;
imshow(BW)
fprintf('Numbers of coins: %d\n',size(centers,1))

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