OpenCV Python 강좌 - 10. Harris Corner Detection

이미지에서 코너 검출시 사용하는 해리스 코너에 대해 알아봅니다.

Harris Corner Detector 구현 코드입니다.

import cv2 as cv import numpy as np import time img_color = cv.imread('chessboard.jpg', cv.IMREAD_COLOR) img_gray = cv.cvtColor(img_color, cv.COLOR_BGR2GRAY) img_sobel_x = cv.Sobel(img_gray, cv.CV_32F, 1, 0) img_sobel_y = cv.Sobel(img_gray, cv.CV_32F, 0, 1) IxIx = img_sobel_x * img_sobel_x IyIy = img_sobel_y * img_sobel_y IxIy = img_sobel_x * img_sobel_y height, width = img_color.shape[:2] window_size = 5 offset = int(window_size/2) r = np.zeros(img_gray.shape) start = time.clock() for y in range(offset, height-offset):    for x in range(offset, width-offset):        window_IxIx = IxIx[y-offset:y+offset+1, x-offset:x+offset+1]        window_IyIy = IyIy[y-offset:y+offset+1, x-offset:x+offset+1]        window_IxIy = IxIy[y-offset:y+offset+1, x-offset:x+offset+1]        Mxx = window_IxIx.sum()        Myy = window_IyIy.sum()        Mxy = window_IxIy.sum()        det = Mxx*Myy - Mxy*Mxy        trace = Mxx + Myy        r[y,x] = det - 0.04 * (trace ** 2) cv.normalize(r,r,0.0,1.0,cv.NORM_MINMAX) for y in range(offset, height-offset):    for x in range(offset, width-offset):        if r[y, x] > 0.4:            img_color.itemset((y, x, 0), 0)            img_color.itemset((y, x, 1), 0)            img_color.itemset((y, x, 2), 255) end = time.clock() print(end-start) cv.imshow("original", img_color) cv.waitKey(0)

OpenCV 함수 cornerHarris 사용 예제입니다.

import numpy as np import cv2 as cv filename = 'shape.jpg' img = cv.imread(filename) gray = cv.cvtColor(img,cv.COLOR_BGR2GRAY) gray = np.float32(gray) dst = cv.cornerHarris(gray, 5, 3, 0.04) #result is dilated for marking the corners, not important dst = cv.dilate(dst,None) # Threshold for an optimal value, it may vary depending on the image. img[dst>0.01*dst.max()]=[0,0,255] cv.imshow('dst',img) if cv.waitKey(0) & 0xff == 27:    cv.destroyAllWindows()

테스트에 사용한 이미지입니다.