CVPR MATLAB

correlation.m

I = imread('dog.jpg');
I = rgb2gray(I);

X = [1 0 0; 
    0 1 0; 
    0 0 1];



Z = sohan_conv(I,X);
imshow(I);
figure,imshow(Z);

function y = sohan_conv(A,X)
X = sohan_xflip(X);
X = sohan_yflip(X);
Z = sohan_correlation(A,X);

y = Z;
end


function y = sohan_yflip(X)
y = [ X(3,1) X(3,2), X(3,3); X(2,1) X(2,2), X(2,3); X(1,1) X(1,2), X(1,3)];
end

function y = sohan_xflip(X)
y = [ X(1,3) X(1,2) X(1,1); X(2,3) X(2,2) X(2,1); X(3,3) X(3,2) X(3,1)];
end

function y = sohan_correlation(A,X)
[rows,cols] = size(A);
rows = rows -1;
cols = cols - 1;

for row = 2:(rows)
    for col = 2:(cols)

       i = A(row-1,col-1) * X(1,1);
       i = i + A(row-1,col) * X(1,2);
       i = i + A(row-1,col+1) * X(1,3);
       
       i = i + A(row,col-1) * X(2,1);
       i = i + A(row,col) * X(2,2);
       i = i + A(row,col+1) * X(2,3);
       
       i = i + A(row+1,col-1) * X(3,1);
       i = i + A(row+1,col) * X(3,2);
       i = i + A(row+1,col+1) * X(3,3);
      
       Y(row,col) = ceil(abs(i));
    end
end
y = Y;
end

harris.m

InputImg = imread('3d-sahpes.jpg');
%InputImg = imread('dog4.jpg');

img = imresize(InputImg, [400 400]);
img = rgb2gray(img);

height = size(img,1);
width = size(img,2);

[xx, yy] = meshgrid(-3:3, -3:3);
sigma = 1;

Gxy = exp(-(xx .^ 2 + yy .^ 2) /2);
Gx = xx .* exp(-(xx .^ 2 + yy .^ 2) / (2 * sigma ^ 2));
Gy = yy .* exp(-(xx .^ 2 + yy .^ 2) / (2 * sigma ^ 2));



Ix = conv2(Gx, img);
Iy = conv2(Gy, img);

Ix2 = Ix .^ 2;
Iy2 = Iy .^ 2;
Ixy = Ix .* Iy;

Rvals = zeros(height,width);

total = 0; 
count = 0;
margin = 4;

for i = margin:height-margin
    for j = margin:width-margin
        M = [
                Ix2(i,j) Ixy(i,j);
                Ixy(i,j) Iy2(i,j)
            ]; 
       
        %detM = det(M);
        detM = M(1,1) * M(2,2) - M(1,2) * M(2,1);
        traceR =  - 0.01*(trace(M))^2;
        Rvals(i,j) = detM - traceR;
        
        if Rvals(i,j) > 0
            total = total + Rvals(i,j);
            count = count + 1;
        end
    end
end



threshold = (total/(count * .08)) ;
imshow(img);
hold on
for i = margin:height-margin
    for j = margin:width-margin
        if Rvals(i,j) > threshold && Rvals(i,j) > Rvals(i,j-1) && Rvals(i,j) > Rvals(i,j+1) && Rvals(i,j) > Rvals(i-1,j-1) && Rvals(i,j) > Rvals(i-1,j) && Rvals(i,j) > Rvals(i-1,j+1) && Rvals(i,j) > Rvals(i+1,j-1) && Rvals(i,j) > Rvals(i+1,j) && Rvals(i,j) > Rvals(i+1,j+1)
            plot(j,i,'gx')
        end
    end
end