clc; clear; close all;% Specify the folder where the files live.
myFolder = 'C:\Users\nazem_000\Desktop\fotos\healthy';% Check to make sure that folder actually exists. Warn user if it doesn't.
if ~isdir(myFolder) errorMessage = sprintf('Error: The following folder does not exist:\n%s', myFolder); uiwait(warndlg(errorMessage)); return;end% Get a list of all files in the folder with the desired file name pattern.
filePattern = fullfile(myFolder, '*.jpg'); % Change to whatever pattern you need.
theFiles = dir(filePattern);for k = 1 : length(theFiles) baseFileName = theFiles(k).name; fullFileName = fullfile(myFolder, baseFileName); fprintf(1, 'Now reading %s\n', fullFileName); % Now do whatever you want with this file name,
% such as reading it in as an image array with imread()
A= imread(fullFileName); % segment the entire fruit
[BW,maskedRGBImage] = createMask2(A);% color image
[BWfilled,properties] = filterRegions2(BW);%%
% segment defect
[BWd,df] = segmentImage21(maskedRGBImage);% defect properties
statsd = regionprops(BWd, 'Area');statsF = regionprops(BWfilled, 'Area');AreaD = cat(1,statsd.Area);AreaF = cat(1,statsF.Area);percDef = 100*AreaD/AreaF;%%% featureextraction (texture)
% Create the Gray Level Cooccurance Matrices (GLCMs)
gray = rgb2gray(A);% Create the Gray Level Cooccurance Matrices (GLCMs)glcms = graycomatrix(gray);% Derive Statistics from GLCM
stats = graycoprops(glcms,'Contrast Correlation Energy Homogeneity');Contrast = stats.Contrast;Correlation = stats.Correlation;Energy = stats.Energy;Homogeneity = stats.Homogeneity;%%% featureextraction (color)
Mean = mean2(maskedRGBImage);Standard_Deviation = std2(maskedRGBImage);Entropy = entropy(maskedRGBImage);RMS = mean2(rms(maskedRGBImage));%%% feature variables
Ex = [Contrast Correlation Energy Homogeneity Mean Standard_Deviation Entropy RMS]; % Display image.
drawnow; % Force display to update immediately.
xlswrite('C:\Users\nazem_000\Desktop\fotos\healthy\healthy1.xls',Ex)end
MATLAB: I have 100 images in a folder ,i want to extra the features glcm ,the code reads all the images but only returns features for one image,and i want to save fin excel for later do classification can someone help
image processing
Best Answer