Detecting Harris corners

Let's start by finding corners using the Harris corner detection algorithm. We will do this by implementing an example. If you continue to study OpenCV beyond this book, you will find that chessboards are a common subject of analysis in computer vision, partly because a checkered pattern is suited to many types of feature detection, and partly because chess is a popular pastime, especially in Russia, where many of OpenCV's developers live.

Here is our sample image of a chessboard and chess pieces:

OpenCV has a handy function called cv2.cornerHarris, which detects corners in an image. We can see this function at work in the following basic example:

import cv2

img = cv2.imread('../images/chess_board.png')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
dst = cv2.cornerHarris(gray, 2, 23, 0.04)
img[dst > 0.01 * dst.max()] = [0, 0, 255]
cv2...