dlib C++ Library - hough_transform_ex.cpp

// The contents of this file are in the public domain. See LICENSE_FOR_EXAMPLE_PROGRAMS.txt
/*
 This is an example illustrating the use of the Hough transform tool in the
 dlib C++ Library.
 In this example we are going to draw a line on an image and then use the
 Hough transform to detect the location of the line. Moreover, we do this in
 a loop that changes the line's position slightly each iteration, which gives
 a pretty animation of the Hough transform in action.
*/
#include <dlib/gui_widgets.h>
#include <dlib/image_transforms.h>
using namespace dlib;
int main()
{
 // First let's make a 400x400 image. This will form the input to the Hough transform.
 array2d<unsigned char> img(400,400);
 // Now we make a hough_transform object. The 300 here means that the Hough transform
 // will operate on a 300x300 subwindow of its input image. 
 hough_transform ht(300);
 image_window win, win2;
 double angle1 = 0;
 double angle2 = 0;
 while(true)
 {
 // Generate a line segment that is rotating around inside the image. The line is
 // generated based on the values in angle1 and angle2. So each iteration creates a
 // slightly different line.
 angle1 += pi/130;
 angle2 += pi/400;
 const point cent = center(get_rect(img)); 
 // A point 90 pixels away from the center of the image but rotated by angle1.
 const point arc = rotate_point(cent, cent + point(90,0), angle1); 
 // Now make a line that goes though arc but rotate it by angle2.
 const point l = rotate_point(arc, arc + point(500,0), angle2);
 const point r = rotate_point(arc, arc - point(500,0), angle2);
 // Next, blank out the input image and then draw our line on it.
 assign_all_pixels(img, 0);
 draw_line(img, l, r, 255);
 
 const point offset(50,50);
 array2d<int> himg;
 // pick the window inside img on which we will run the Hough transform.
 const rectangle box = translate_rect(get_rect(ht),offset);
 // Now let's compute the hough transform for a subwindow in the image. In
 // particular, we run it on the 300x300 subwindow with an upper left corner at the
 // pixel point(50,50). The output is stored in himg.
 ht(img, box, himg);
 // Now that we have the transformed image, the Hough image pixel with the largest
 // value should indicate where the line is. So we find the coordinates of the
 // largest pixel:
 point p = max_point(mat(himg));
 // And then ask the ht object for the line segment in the original image that
 // corresponds to this point in Hough transform space.
 std::pair<point,point> line = ht.get_line(p);
 // Finally, let's display all these things on the screen. We copy the original
 // input image into a color image and then draw the detected line on top in red.
 array2d<rgb_pixel> temp;
 assign_image(temp, img);
 // Note that we must offset the output line to account for our offset subwindow.
 // We do this by just adding in the offset to the line endpoints. 
 draw_line(temp, line.first+offset, line.second+offset, rgb_pixel(255,0,0));
 win.clear_overlay();
 win.set_image(temp);
 // Also show the subwindow we ran the Hough transform on as a green box. You will
 // see that the detected line is exactly contained within this box and also
 // overlaps the original line.
 win.add_overlay(box, rgb_pixel(0,255,0));
 // We can also display the Hough transform itself using the jet color scheme.
 win2.set_image(jet(himg));
 }
}