i am doing work on detection of malarial parasite. red blood cell extraction is the part of this project.
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sana saleeme
il 1 Feb 2016
Commentato: Image Analyst
il 17 Feb 2016
i am doing work on detection of malarial parasite. red blood cell extraction is the part of this project. description is that
where g(m,n) is m rows by n columns 24 bit color image obtained after RBC extraction, x(m,n,l) is the 8 bit red color plane in x(m,n), x(m,n,2) is the 8 bit green color plane in x(m,n), x(m,n,3) is the 8 bit blue color plane in x(m,n), can anyone convert it into matlab code?
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Star Strider
il 2 Feb 2016
Include one of your images, whether they’re sporozoites or merozoites, and the species: P. falciparium, P. vivax, P. knowlesi, or P. malariae.
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Image Analyst
il 2 Feb 2016
Try this:
% Extract the individual red, green, and blue color channels.
redChannel = rgbImage(:, :, 1);
greenChannel = rgbImage(:, :, 2);
blueChannel = rgbImage(:, :, 3);
redMask = redChannel >= 170;
greenMask = greenChannel >= 150 & greenChannel <= 201;
blueMask = blueChannel >= 160 & blueChannel <= 220;
mask = redMask & greenMask & blueMask;
% Mask channels
redChannel(~mask) = 255;
greenChannel(~mask) = 255;
blueChannel(~mask) = 255;
% Recombine separate masked color channels into a single, true color RGB image.
maskedRgbImage = cat(3, redChannel, greenChannel, blueChannel);
% maskedRgbImage is what the paper calls "g"
This code won't work unless your color gamut is the same as what they have. In other words if the color temperature (white balance) of your lighting and the exposure (brightness) don't match their values, then you'd need to use different threshold numbers. I usually don't like color segmentation in RGB space because of those reasons, unless you know that you will have very reproducible/stable lighting and subject.
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Image Analyst
il 17 Feb 2016
I don't know what to say. What image? Just try it and see. Adapt it as needed.
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