1) Understanding Hough Transform

- Implement Hough Transform (sample code is given at the lecture notes.) by using your own Canny Edge Detect code and execute it for different images given. - Learn Matlab’s embedded Hough Tranform function. Explain its parameters with outputs of your own selfie. - Compare results with your own code and explain if there is any differences.

sample code

clear % Creating a simple image im = Get your selfie and use given images. figure imshow(im) %% Initializing other parameters theta = ((-90:90)./180) .* pi; D = sqrt(size(im,1).^2 + size(im,2).^2); HS = zeros(ceil(2.*D),numel(theta)); [y,x] = find(im); y = y - 1; x = x - 1; figure rho = cell(1,numel(x)); %% Calculating the Hough Transform for i = 1: numel(x) rho{i} = x(i).*cos(theta) + y(i).*sin(theta); % [-sqrt(2),sqrt(2)]*D rho interval plot(theta,-rho{i}) hold on end %% Creating the Hough Space as an Image

for i = 1:numel(x) rho{i} = rho{i} + D; % mapping rho from 0 to 2*sqrt(2) rho{i} = floor(rho{i}) + 1; for j = 1:numel(rho{i}) HS(rho{i}(j),j) = HS(rho{i}(j),j) + 1; end end figure imshow(HS)