PCA_shapes.asv

sizzz=zeros(1,320);
pC=[];
for i = 1:60
    %Reading image one by one 
    %convert rgb image into grayscale
    I1 = rgb2gray(imread(strcat('shapes/',strcat(int2str(i),'.png'))));
    
    %features extraction using SURF algorithms
    points1 = detectSURFFeatures(I1);
    [features1,valid_points1] = extractFeatures(I1,points1);

    %Dimensionality reduction of extracted features using PCA 
    [pca1,zscore]=pca(features1);

    %Converting matrix into 1-dimension vector of size 320(5 Principal components)
    %Padding the smaller sized vector with '0'
    B = reshape(pca1,[],1);
    B(320)=0;

    %Transformed inputs for classification 
    pC(:,i)=B(1:320);
    sizzz(i)=size(pca1,2);

end


sizzz
pC
size(pC);