参考链接：https://www.cnblogs.com/babycomeon/p/13112687.html

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开运算：先腐蚀，再膨胀

例子：

待处理图像

　　　　　　

 

 目标：取出电路图，消除标注

import cv2
import numpy as np
import matplotlib.pyplot as plt

S = cv2.imread('Source.jpg',0)

plt.rcParams['font.sans-serif']=['SimHei']
plt.rcParams['axes.unicode_minus']=False
#plt.imshow(S,'gray'), plt.title('电路原图')

#构造开运算结构元素
struct_1 = np.zeros((15,15),np.uint8)
struct_2 = struct_1.copy()
struct_1[7,...] = 1
struct_2[...,7] = 1
struct_3 = np.identity(9,np.uint8)
struct_4 = np.fliplr(struct_3)
s_5 = np.identity(3,np.uint8)
s_6 = np.fliplr(s_5)

#水平方向腐蚀、膨胀
Row = cv2.erode(S,struct_1,iterations = 1)  
Row = cv2.dilate(Row,struct_1,iterations = 1) 
#竖直方向腐蚀、膨胀
Col = cv2.erode(S,struct_2,iterations = 1)  
Col = cv2.dilate(Col,struct_2,iterations = 1) 
#右斜方向腐蚀、膨胀
Right = cv2.erode(S,struct_3,iterations = 1)  
Right = cv2.dilate(Right,s_5,iterations = 1) 
#左斜方向腐蚀、膨胀
Left = cv2.erode(S,struct_4,iterations = 1)
Left = cv2.dilate(Left,s_6,iterations = 1)

Img_out = Row + Col + 2*Right + 2*Left

plt.imshow(Img_out,'gray'), plt.title('腐蚀图')
cv2.imwrite('out.bmp',Img_out)

结果：