MATLAB: How to detect skin region in YCbCr color space

image processingImage Processing Toolbox

I want to detect skin region in images which contain hand, foot or mouth and remove the background. The YCbCr color space is used in my work. I can convert the image into YCbCr color space and split each color channel in this color space but could go further. I have attached an image shows the original image and the detected skin region which I want (It was performed in a paper).
Any help would be deeply appriciated.
Here is some of my code:
% Read image
imgRGB = imread('ColorSpace\hand_foot12.jpg');
% Convert to YCbCr
YCbCr = rgb2ycbcr(imgRGB);
% Split each channel
Y=YCbCr( :,:,1);
Cb=YCbCr( :,:,2);
Cr=YCbCr( :,:,3);
orig_detect.JPG

Best Answer

Hi,
You can use ‘Color Thresholder’ app provided in the Image Acquisition Toolbox.
  1. After loading the image from a file/workspace, you can choose a color space for the image. Since you want to extract purple and yellow colours, I would recommend you to use YCbCr for purple colour and RGB space for the yellow colour.
  2. You would then see the image along with a set of controls for each colour component, depending on the colour space chosen. Adjust these controls to get the colour you want. And ‘Export Function’ for the resultant image.
  3. By exporting to function, you get Min and Max values for each channel for both the colours (yellow and Purple). You would also get a sliderBW matrix in each function. Use logical operator || to include both the matrices in your workspace and then set these pixels to white colour.
You can also refer to an example for purple colour from the documentation provided in the link.
Below is the code for an image file named ‘peppers.png’ and may need to be changed in some cases - 
% Load your image in RGB variable 
% Convert RGB image to chosen color space 
I = RGB; 
  
% Define thresholds for channel 1 based on histogram settings 
channel1Min = 53.000; 
channel1Max = 178.000; 
  
% Define thresholds for channel 2 based on histogram settings 
channel2Min = 55.000; 
channel2Max = 153.000; 
  
% Define thresholds for channel 3 based on histogram settings 
channel3Min = 37.000; 
channel3Max = 142.000; 
  
% Create mask based on chosen histogram thresholds 
sliderBW = (I(:,:,1) >= channel1Min ) & (I(:,:,1) <= channel1Max) & ... 
    (I(:,:,2) >= channel2Min ) & (I(:,:,2) <= channel2Max) & ... 
    (I(:,:,3) >= channel3Min ) & (I(:,:,3) <= channel3Max); 
BW = sliderBW; 
  
% Initialize output masked image based on input image. 
maskedRGBImage = RGB; 
  
% Set background pixels where BW is false to zero. 
maskedRGBImage(repmat(~BW,[1 1 3])) = 0;
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