Is there a way to overlay one mask onto another?

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Teshan Rezel 2021-8-4

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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/892402-is-there-a-way-to-overlay-one-mask-onto-another

编辑： Teshan Rezel 2021-8-4

1.png
3.png

I have two masks, as below. I want to make sure that the white area of the second mask is not more than the white in the first. Is there a way to overlay mask 1 over mask 2?

In other words, mask 1 is the mnaximum possible size of the obejct of interest, whilst mask 2 is guaranteed to be smaller than mask 1. Mask 2, however, has artifacts (remnants of the background from thresholding). I would like to "screen out" the background from mask 2, to overlay the black elements of mask 1 onto mask 2 so that mask 2 is at most as big as mask 1.

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the cyclist 2021-8-4

Can you upload the two image files?

Teshan Rezel 2021-8-4

@the cyclist done, thanks!

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Answer 1

the cyclist 2021-8-4

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https://ww2.mathworks.cn/matlabcentral/answers/892402-is-there-a-way-to-overlay-one-mask-onto-another#answer_760987

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I don't really do image processing, but I think this straightforwardly answers your question, using only base MATLAB commands. There might be simpler ways, using the Image Processing Toolbox.

% Upload the image
image1 = imread('https://www.mathworks.com/matlabcentral/answers/uploaded_files/703072/1.png');
image3 = imread('https://www.mathworks.com/matlabcentral/answers/uploaded_files/703077/3.png');
% Check if a pixel is white (i.e. all values are 255)
isWhitePixel1 = all(image1==255,3);
isWhitePixel3 = all(image3==255,3);
% Count the number of white pixels in each image
numberWhitePixels1 = sum(isWhitePixel1(:));
numberWhitePixels3 = sum(isWhitePixel3(:));
% Because the image are different sizes, calculate the fraction of the
% image that is white rather than the pixel count.
fractionalWhiteArea1 = 3*numberWhitePixels1/prod(size(image1))
fractionalWhiteArea1 = 0.9499
fractionalWhiteArea3 = 3*numberWhitePixels3/prod(size(image3))
fractionalWhiteArea3 = 0.9601

You can see that image 1 has about 95% white area, and image 3 has about 96%. Note that image 3 has some gray values ([191,191,191]), but image 1 has only black and white.