ssa

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function [out, bin] = skinmap(img_orig)
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%   The function reads an image file given by the input parameter string
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%   filename, read by the MATLAB function 'imread'.
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%   out - contains the skinmap overlayed onto the image with skin pixels
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%   marked in blue color.
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%   bin - contains the binary skinmap, with skin pixels as '1'.
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%    
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    if nargin > 1 || nargin < 1
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        error('usage: generate_skinmap(image)');
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    end
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    %Read the image, and capture the dimensions
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    height = size(img_orig,1);
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    width = size(img_orig,2);
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    %Initialize the output images
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    out = img_orig;
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    bin = zeros(height,width);
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         img = img_orig;
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    %Apply Grayworld Algorithm for illumination compensation
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%     Êîìïåíñàöèÿ ÿðêîñòè
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% figure(); imshow(img_orig); title('Èñõîäíîå ôîòî');
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%             A_lin = rgb2lin(img_orig);
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%             percentiles = 10;
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%             illuminant = illumgray(A_lin,percentiles);
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%             B_lin = chromadapt(A_lin,illuminant,'ColorSpace','linear-rgb');
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%             img = lin2rgb(B_lin);
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% figure(); imshow(img); title('Îáðàáîòàííîå ôîòî');
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    %Convert the image from RGB to YCbCr
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    img_ycbcr = rgb2ycbcr(img);
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    Cb = img_ycbcr(:,:,2);
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    Cr = img_ycbcr(:,:,3);
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    %Convert to HUE
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    [hue,~,~] = rgb2hsv(img);
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    %Detect Skin
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    [r,c,~] = find(Cb>=98 & Cb<=142 & Cr>=135 & Cr<=177 & hue<=0.1 & 0.01<=hue);
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    numind = size(r,1);
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    %Mark Skin Pixels
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    for i=1:numind
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        out(r(i),c(i),:) = [0 0 255];
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        bin(r(i),c(i)) = 1;
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    end
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end
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