MATLAB: What is purpose of the target varriable

image processing

function [Instances T_target]=create_learning_set()
%% create data set for each texture class
%for cloud class
srcFiles = dir('colored_textures\LearningSet\cloud\*.jpg'); % the folder in which images exists
Iin=[]; %this hold the data as input to the neural network
Target=[]; %this holds the target or the required result for each class, we put it manully.
%read the folder containing the cloud images
for i = 1 : length(srcFiles) % determins how many images are there in the folder, this loop will be executed 3 times because cloud folder has 3 images
    filename = strcat('colored_textures\LearningSet\cloud\',srcFiles(i).name); %this will include the filename after the directory name
    I = imread(filename); %read the image
    F=get_image_features(I); %create feature vector for the image




    Iin=[Iin F']; %concatenate the feature vector to the store of features




    Target=[Target, 100];%concatenate the target value for each feature vector




end
%for gravel class
srcFiles = dir('colored_textures\LearningSet\gravel\*.jpg'); % the folder in which ur images exists
for i = 1 : length(srcFiles)
    filename = strcat('colored_textures\LearningSet\gravel\',srcFiles(i).name);
    I = imread(filename);
     F=get_image_features(I); %create feature vector for the image
    Iin=[Iin F']; %concatenate the feature vector to the store of features
    Target=[Target, 200];%concatenate the target value for each feature vector
end
%for wood class
srcFiles = dir('colored_textures\LearningSet\wood\*.jpg'); % the folder in which ur images exists
for i = 1 : length(srcFiles)
    filename = strcat('colored_textures\LearningSet\wood\',srcFiles(i).name);
    I = imread(filename);
    F=get_image_features(I); %create feature vector for the image
    Iin=[Iin F']; %concatenate the feature vector to the store of features
    Target=[Target, 300];%concatenate the target value for each feature vector
end
%for jute class
srcFiles = dir('colored_textures\LearningSet\jute\*.jpg'); % the folder in which ur images exists
for i = 1 : length(srcFiles)
    filename = strcat('colored_textures\LearningSet\jute\',srcFiles(i).name);
    I = imread(filename);
    F=get_image_features(I); %create feature vector for the image
    Iin=[Iin F']; %concatenate the feature vector to the store of features
    Target=[Target, 500];%concatenate the target value for each feature vector
end
%for water class
srcFiles = dir('colored_textures\LearningSet\water\*.jpg'); % the folder in which ur images exists
for i = 1 : length(srcFiles)
    filename = strcat('colored_textures\LearningSet\water\',srcFiles(i).name);
    I = imread(filename);
    F=get_image_features(I); %create feature vector for the image
    Iin=[Iin F']; %concatenate the feature vector to the store of features
    Target=[Target, 600];%concatenate the target value for each feature vector
end
%for sanke class
srcFiles = dir('colored_textures\LearningSet\sanke\*.jpg'); % the folder in which ur images exists
for i = 1 : length(srcFiles) filename = strcat('colored_textures\LearningSet\sanke\',srcFiles(i).name); I = imread(filename); F=get_image_features(I); %create feature vector for the image Iin=[Iin F']; %concatenate the feature vector to the store of features Target=[Target, 700];%concatenate the target value for each feature vector end
T_target=Target;
Instances=Iin;
end

Best Answer

It is an arbitrary class (group) number to distinguish between the classes. All members of the same class of textures are given the same class number (target)
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