MATLAB: Feature extraction for classification

classificationComputer Vision Toolboxfeature extractionfruitImage Processing Toolbox

Hi there, I attached the images that I want to extract features for classification. these are zoomed images of different fruits. kindly help me how to find features on these images. I tried using extractHOGfeatures function but its not giving me correct classification.

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I would think that just color (Hue and Saturation) and texture might be enough. Of course if two images look the same but are different fruits, there is no telling, like you have an image of orange grainy things and one is an apricot and one is a nectarine.

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MATLAB: Creation of a mask on RGB image

Instead of multiplying pixels in the mask by a constant value, you can mulitply all pixels by an "image" of the saturation multiplier.

So rather than the scalar "1.6", which could as well have been a element-by-element multiplication, your original strategy could have been executed as

[M,N] = size(Imm)
satFactorMat = 1.6*ones(M,N);
satFactorMat(binaryImage) = 1.6;
saturationImage = saturationImage .* satFactorMat;

So now hopefully it is clear you don't really need the mask concept for the operation of altering the image itself, you just might use it to define the satFactorMat "topography", which looks like a mesa.Now you can just smooth it out using something like a smoothing function; you can use imgaussfilt

satFactorMat = imgaussfilt(satFactorMat,6);

You may need to convert everything to doubles first before doing the imgaussfilt and elementwise multiplication, and then convert back to uint8.

Also, note that multiplying is dangerous because you may end up with values outside valid range (>255). So it would be safe to exponentiate (but then you have to normalize your pixel values onto (0,1) first.

hsvImage = double(hsvImage)/255;
% ... everythign in between
% except instead of multiply by satFactorMat, you can do something like
satPowerMat = ones(M,N);
satPowerMat(binaryImage) = 0.3;
satPowerMat = imgaussfilt(satPowerMat,6);
saturationImage = saturationImage .* satPowerMat;
% Recombine
hsvImage = cat(3, hueImage, saturationImage, valueImage);
hsvImage = uint8(hsvImage*255);

MATLAB: How to calculate GLDS texture features

Use graycoprops() and graycomatrix() in the Image Processing Toolbox.

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MATLAB: Creation of a mask on RGB image

MATLAB: How to calculate GLDS texture features

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