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How to detect skin region in YCbCr color space?

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How to detect skin region in YCbCr color space?

johnwilson92 asked: skin region, image processing,matlab

Learn how to detect skin regions in images using the YCbCr color space with MATLAB! This resource provides a step-by-step guide and code examples. Start detecti

Expert Answer

Profile picture of Prashant Kumar Prashant Kumar answered . 2025-08-18 12:21:36

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.

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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