MATLAB: Image processing: segmentation of region of interest
color segmentationcolour based segmentationcropping imagedigital image processingImage Processing Toolbox
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I do that in my HSV color segmentation demo in my file Exchange: http://www.mathworks.com/matlabcentral/fileexchange/?term=authorid%3A31862
Also search the forum for tag:fruit since fruit analysis seems to be one of the most popular subjects for student projects.
I would reccomend using the Color Thresholder App which is part of the Image Processing Toolbox. You can load in an image either from a GUI or from your workspace (use imread).
Use HSV color space and adjust your V value as you want the darker region.
Your MATLAB script would look something like this:
I = imread('image1.jpg');[BW,maskedRGBImage] = createMask(I);imshow(BW)Where the createMask function is autogenerated from the app:
function [BW,maskedRGBImage] = createMask(RGB)%createMask Threshold RGB image using auto-generated code from colorThresholder app.
% [BW,MASKEDRGBIMAGE] = createMask(RGB) thresholds image RGB using
% auto-generated code from the colorThresholder app. The colorspace and
% range for each channel of the colorspace were set within the app. The
% segmentation mask is returned in BW, and a composite of the mask and
% original RGB images is returned in maskedRGBImage.
% Auto-generated by colorThresholder app on 13-Nov-2018
%------------------------------------------------------
% Convert RGB image to chosen color space
I = rgb2hsv(RGB);% Define thresholds for channel 1 based on histogram settings
channel1Min = 0.000;channel1Max = 1.000;% Define thresholds for channel 2 based on histogram settings
channel2Min = 0.000;channel2Max = 1.000;% Define thresholds for channel 3 based on histogram settings
channel3Min = 0.000;channel3Max = 0.236;% 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;endThe result is (in black and white):
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