How can apply the Hough transform to detect lines in an images?

%% Find lines and plot them lines = houghlines(imEdge,T,R,P,'FillGap',30,'MinLength',15); figure, imshow(im), 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
%imclearborder
% highlight the longest line segment
plot(xy_long(:,1),xy_long(:,2),'LineWidth',2,'Col

Answer 1

[Aniket]

Hi @sonia carole,

The code you have provided uses the peaks from the Hough Transform to extract lines using houghlines and then plots all the detected lines. Please find below a brief explation to detect edges and compute the Hough Transform:

• Convert image to grayscale

im = imread('image.jpeg');
gray = rgb2gray(im);

• Detect Edges

imEdge = edge(gray, 'Canny');

• Compute the Hough Transform

[H, T, R] = hough(imEdge);

• Identify peaks in Hough Transform

P = houghpeaks(H, 10, 'Threshold', ceil(0.3 * max(H(:))));

• Extract Lines and plot them: This is same as the code provided by you.

lines = houghlines(imEdge, T, R, P, 'FillGap', 30, 'MinLength', 15);
figure, imshow(im), 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 endpoints
    plot(xy(1,1), xy(1,2), 'x', 'LineWidth', 2, 'Color', 'yellow');
    plot(xy(2,1), xy(2,2), 'x', 'LineWidth', 2, 'Color', 'red');
    
    % Keep track of the longest line
    len = norm(lines(k).point1 - lines(k).point2);
    if len > max_len
        max_len = len;
        xy_long = xy;
    end
end

% Highlight the longest line
plot(xy_long(:,1), xy_long(:,2), 'LineWidth', 2, 'Color', 'blue');

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You may modify the code based on your requirements (Horizontal lines/ removing short lines etc.)

You may also use Hough Transform block from Computer Vision Toolbox which inputs an image and returns the Hough Transform: https://www.mathworks.com/help/vision/ref/houghtransform.html

I hope this helps!