The Hough transform is one of the most important topics of computer vision. It is used in feature extraction and image analysis. The Hough transform was invented in 1972 by Richard Duda and Peter Hart, and it was originally called the generalized Hough transform. In general, the technique is used to find instances of objects that are not perfectly within a certain class by means of a voting procedure.Â
We can use the Hough transform along with region of interest masking. We will see an example of the detection of road markings in Chapter 5, Finding Road Markings Using OpenCV, using the Hough transform and region of interest masking together.
We will learn about the Hough transform in more detail with the drawing of a 2D coordinate space of x and y inside a straight line, as shown in Fig 4.74.
We know that the equation of a straight line is . The straight line has two parameters, m and c, and we are currently plotting it...