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    %% Detect Lines in Images Using Hough 
% This example shows how to detect lines in an image using the |hough|
% function.
%%
% Read an image into the workspace and, to make this example more
% illustrative, rotate the image. Display the image.
I = imread('circuit.tif');
rotI = imrotate(I,33,'crop');
imshow(rotI)
%%
% Find the edges in the image using the |edge| function. 
BW = edge(rotI,'canny');
imshow(BW);
%%
% Compute the Hough transform of the binary image returned by |edge|.
[H,theta,rho] = hough(BW);
%%
% Display the transform, |H|, returned by the |hough| function.
figure
imshow(imadjust(mat2gray(H)),[],...
       'XData',theta,...
       'YData',rho,...
       'InitialMagnification','fit');
xlabel('\theta (degrees)')
ylabel('\rho')
axis on
axis normal 
hold on
colormap(hot)
%%
% Find the peaks in the Hough transform matrix, |H|, using the |houghpeaks|
% function.
P = houghpeaks(H,5,'threshold',ceil(0.3*max(H(:))));
%%
% Superimpose a plot on the image of the transform that identifies the
% peaks.
x = theta(P(:,2));
y = rho(P(:,1));
plot(x,y,'s','color','black');
%%
% Find lines in the image using the |houghlines| function. 
lines = houghlines(BW,theta,rho,P,'FillGap',5,'MinLength',7);
%%
% Create a plot that displays the original image with the lines
% superimposed on it.
figure, imshow(rotI), hold on
max_len = 0;
for k = 1:length(lines)
   xy = [lines(k).point1; lines(k).point2];
   plot(xy(:,1),xy(:,2),'LineWidth',2,'Color','green');

   % Plot beginnings and ends of lines
   plot(xy(1,1),xy(1,2),'x','LineWidth',2,'Color','yellow');
   plot(xy(2,1),xy(2,2),'x','LineWidth',2,'Color','red');

   % Determine the endpoints of the longest line segment
   len = norm(lines(k).point1 - lines(k).point2);
   if ( len > max_len)
      max_len = len;
      xy_long = xy;
   end
end
% highlight the longest line segment
plot(xy_long(:,1),xy_long(:,2),'LineWidth',2,'Color','red');