Hi, it is not so difficult, the basic steps are the following:
- Convert image to grayscale (cvtColor function).
- Apply an edge detector (Canny or Sobel, for example) to obtain a binary image (0 on the background, 1 on edges).
- Run the Probabilistic Hough Line Transform (better suited for finding few long lines) with the HoughLinesP function to obtain a vector of lines (you have to tweak the parameters to accomodate your scenario).
- Iterate through this vector to keep only lines with angles similar to 0° or 90° (supposing your page is almost perpendicular to axes).
- For each pair of lines with perpendicular angles, find the intersection point (here is better to solve the equivalent system of line equations for more robustness).
- You have a bunch of points for each of the four page corners, you must run a distance threshold filtering to merge them to obtain at most 4 of them.
Two excellent tutorials for the first three steps are part of the OpenCV documentation and you can find here and here.
