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In one question in which I wanted to calculate the dark (black) area in a binary image, you guys answered to me:

"If all you need is the area of the dark region then you don't need to find the edge at all. You just need to threshold and sum

binaryImage = grayImage < 128; % or whatever.

darkArea = sum(binaryImage);

darkArea2 = bwarea(binaryImage); % Another way using different algorithm. "

Now a problem comes to me. I wonder:

We want the area of black region not white, so when we use sum (or bwarea), we are actually calculating the white area region. right? because white pixels are 1 and black ones are 0 and by summing we are summing the white ones not black ones.

Thus, the area of black region should be this:

image_size = size(binary_image)

whole_area = image_size(1)*image_size(2)

white_area = sum(sum(binary_image)); % or

% white_area = bwarea(binary_image);

black_area = whole_area - white_area;

Am I right?

Sorry for such a trivial question, but I was really confused!

Thanks so much.

Image Analyst
on 19 Dec 2013

No, that's not right. It's as I told you at first.

When you do

binaryImage = grayImage < 128; % Find dark pixels. Dark = true, 1, white.

you're creating a matrix that is "true" wherever the image is dark . If you sum that, it treats the "true" pixels as 1, and thus, counts them - counts the dark pixels. So you're getting the sum of the "true/1/white" pixels in the binary image which means your getting the count of the dark pixels of the gray scale image. Doing it your complicated way would count the bright pixels. By the way, if you wanted the binary image to be false where the gray scale image was dark, you'd flip the less than sign and then sum the inverse, which is much simpler than doing the multi-step process you did.

binaryImage = grayImage > 128; % Find bright pixels instead of dark pixels.

numDarkPixels = sum(~binaryImage(:)); % Notice I had to invert the image with~.

Image Analyst
on 19 Dec 2013

Image Analyst
on 25 Dec 2013

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