Tag: performance

I segmented an image in N superpixels and built a graph based on what each super pixel considered as a node. Information about neighboring superpixels is stored in glcms training. The weight between each pair of neighboring superpixels is stored in a matrix W.

Finally, I want to calculate the geodetic distance between non-adjacent superpixels using graphshortestpath function. The following codes perform the aforementioned process, however, it takes a long time. Specifically, the last section of the code that calculates the geodetic distance takes longer than expected (more than 15 seconds).

    Img=imread('input.jpg');
    (rows, columns, numberOfColorChannels) = size(Img);
    (L,N) = superpixels(Img,250);

    %Identifying neighborhood relationships
    glcms = graycomatrix(L,'NumLevels',N,'GrayLimits',(1,N),'Offset',  (0,1;1,0)); %Create gray-level co-occurrence matrix from image
    glcms = sum(glcms,3);    % add together the two matrices
    glcms = glcms + glcms.'; % add upper and lower triangles together, make it symmetric
    glcms(1:N+1:end) = 0;    % set the diagonal to zero, we don't want to see "1 is neighbor of 1"

    data = zeros(N,3);
    for labelVal = 1:N
    redIdx = idx{labelVal};
    greenIdx = idx{labelVal}+numRows*numCols;
    blueIdx = idx{labelVal}+2*numRows*numCols;
    data(labelVal,1) = mean(Img(redIdx));
    data(labelVal,2) = mean(Img(greenIdx));
    data(labelVal,3) = mean(Img(blueIdx));

    end    

   Euc=zeros(N);
% Euclidean Distance
for i=1:N
    for j=1:N
        if glcms(i,j)~=0
            Euc(i,j)=sqrt(((data(i,1)-data(j,1))^2)+((data(i,2)-data(j,2))^2)+((data(i,3)-data(j,3))^2));
        end
    end
end


W=zeros(N);
W_num=zeros(N);

W_den=zeros(N);
OMG1=0.1;
for i=1:N
    for j=1:N
        if(Euc(i,j)~=0)
         W_num(i,j)=exp(-OMG1*(Euc(i,j)));
         W_den(i,i)=W_num(i,j)+W_den(i,i);
        end
    end
end

for i=1:N
    for j=1:N
         if(Euc(i,j)~=0)
             W(i,j)=(W_num(i,j))/(W_den(i,i));   % Connectivity Matrix W

         end
    end
end


s_star_temp=zeros(N);   %temporary variable for geodesic distance measurement
W_sparse=zeros(N);
W_sparse=sparse(W);
for i=1:N
    for j=1:N
        if W(i,j)==0 & i~=j;
            s_star_temp(i,j)=graphshortestpath(W_sparse,i,j); % Geodesic Distance
        end
    end
end

The question is how to optimize the code so that it is more efficient, that is, it requires less time.