环境
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pip install opencv-python==3.4.2.16 pip install opencv-contrib-python==3.4.2.16 |
理论
克里斯·哈里斯（Chris Harris）和迈克·史蒂芬斯（Mike Stephens）在1988年的论文《组合式拐角和边缘检测器》中做了一次尝试找到这些拐角的尝试，所以现在将其称为哈里斯拐角检测器。
函数：cv2.cornerHarris（），cv2.cornerSubPix（）
示例代码
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import cv2import numpy as np filename = 'molecule.png'img = cv2.imread(filename)gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) gray = np.float32(gray)dst = cv2.cornerHarris(gray,2,3,0.04) #result is dilated for marking the corners, not importantdst = cv2.dilate(dst,None) # Threshold for an optimal value, it may vary depending on the image.img[dst>0.01*dst.max()]=[0,0,255] cv2.imshow('dst',img)if cv2.waitKey(0) & 0xff == 27: cv2.destroyAllWindows() |
原图
输出图
SubPixel精度的角落
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import cv2import numpy as np filename = 'molecule.png'img = cv2.imread(filename)gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) # find Harris cornersgray = np.float32(gray)dst = cv2.cornerHarris(gray,2,3,0.04)dst = cv2.dilate(dst,None)ret, dst = cv2.threshold(dst,0.01*dst.max(),255,0)dst = np.uint8(dst) # find centroidsret, labels, stats, centroids = cv2.connectedComponentsWithStats(dst) # define the criteria to stop and refine the cornerscriteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 100, 0.001)corners = cv2.cornerSubPix(gray,np.float32(centroids),(5,5),(-1,-1),criteria) # Now draw themres = np.hstack((centroids,corners))res = np.int0(res)img[res[:,1],res[:,0]]=[0,0,255]img[res[:,3],res[:,2]] = [0,255,0] cv2.imwrite('subpixel5.png',img) |
输出图
参考
https://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_feature2d/py_features_harris/py_features_harris.html#harris-corners
以上就是本文的全部内容，希望对大家的学习有所帮助，也希望大家多多支持服务器之家。
原文链接：https://blog.csdn.net/u012325865/article/details/103044562
