canny edge detection, hough transform and find 10 peaks in matlab in matlab

main.m
% Read in image
img = imread('example_image.jpg');

% Convert to grayscale
gray_img = rgb2gray(img);

% Apply Canny edge detection with default parameters
edge_img = edge(gray_img, 'canny');

% Show the original image and the edge image side by side
figure;
imshowpair(img, edge_img, 'montage');
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main.m
% Read in image
img = imread('example_image.jpg');

% Convert to grayscale
gray_img = rgb2gray(img);

% Apply Canny edge detection to get binary edge image
edge_img = edge(gray_img, 'canny');

% Apply Hough transform to detect lines
[H,theta,rho] = hough(edge_img);

% Show the Hough transform matrix
figure;
imshow(imadjust(mat2gray(H)),[],'XData',theta,'YData',rho,'InitialMagnification','fit');
xlabel('\theta (degrees)'), ylabel('\rho');
axis on, axis normal, hold on;
colormap(gca,hot);

% Find peaks in Hough transform matrix
peaks = houghpeaks(H, 10);
x = theta(peaks(:,2));
y = rho(peaks(:,1));

% Overlay detected lines on original image
figure;
imshow(img), hold on
plot(x,y,'s','color','white');
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main.m
% Read in image
img = imread('example_image.jpg');

% Convert to grayscale
gray_img = rgb2gray(img);

% Apply Canny edge detection to get binary edge image
edge_img = edge(gray_img, 'canny');

% Apply Hough transform to detect lines
[H,theta,rho] = hough(edge_img);

% Find peaks in Hough transform matrix
peaks = houghpeaks(H, 10);
disp(peaks);
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