【快速实践 OpenCV morphology】形态学操作：腐蚀、膨胀、开运算、闭运算
✨我们将以下图为例，快速实践不同的形态学操作，如腐蚀 erode、膨胀 dilate、开 open、闭 close …
import cv2
import numpy as npimg = cv2.imread('D:\Desktop\csdn.png',0)
cv2.imshow('binary_Erode2', img)
cv2.waitKey(0)
💜 腐蚀 ：内核在图像中滑动，当内核下存在(原始图像中的)像素不为 1 时，内核下的区域将被腐蚀 （变为零）
erosion = cv2.erode(img,kernel) ## 白色变小
import cv2
import numpy as npimg = cv2.imread('D:\Desktop\csdn.png',0)kernel = np.ones((10,10),np.uint8)
erosion = cv2.erode(img,kernel) ### cv2.imshow('binary_Erode', erosion)
cv2.waitKey(0)
💜 膨胀 ：内核在图像中滑动，当内核下存在(原始图像中的)像素为 1 时，内核下的区域将被膨胀 （变为一）
dilation = cv2.dilate(img,kernel) ## 白色变大
import cv2
import numpy as npimg = cv2.imread('D:\Desktop\csdn.png',0)kernel = np.ones((10,10),np.uint8)
dilation = cv2.dilate(img,kernel) ### cv2.imshow('binary_Dilation', dilation)
cv2.waitKey(0)
💜 开运算 ：腐蚀再膨胀
opening = cv2.morphologyEx(img, cv2.MORPH_OPEN, kernel)
import cv2
import numpy as npimg = cv2.imread('D:\Desktop\csdn.png',0)kernel = np.ones((10,10),np.uint8)
opening = cv2.morphologyEx(img, cv2.MORPH_OPEN, kernel) ### cv2.imshow('binary_Opening ', opening)
cv2.waitKey(0)
💜 闭运算 ：膨胀再腐蚀
closing = cv2.morphologyEx(img, cv2.MORPH_CLOSE, kernel)
import cv2
import numpy as npimg = cv2.imread('D:\Desktop\csdn.png',0)kernel = np.ones((10,10),np.uint8)
closing = cv2.morphologyEx(img, cv2.MORPH_CLOSE, kernel) ### cv2.imshow('binary_Closing', closing)
cv2.waitKey(0)