Opencv实用操作5 图像腐蚀膨胀

发布于:2025-05-30 ⋅ 阅读:(21) ⋅ 点赞:(0)

相关函数

腐蚀函数

img1_erosion = cv2.erode(img1,kernel,iterations=1)

(图片,卷积核,次数)

膨胀函数

img_dilate = cv2.dilate(img2,kernel1,iterations=1)

(图片,卷积核,次数)

实验代码

#腐蚀膨胀操作,
import matplotlib.pyplot as plt
import cv2
import numpy as np

img1 = cv2.imread("image/dige.png")       #读取图片
img2 = cv2.imread("image/yuan.png")

kernel = np.ones((3,3),np.uint8)  #卷积核
kernel1 = np.ones((30,30),np.uint8)
img1_erosion = cv2.erode(img1,kernel,iterations=1)#(图片,卷积核,次数)
#腐蚀
img2_erosion = cv2.erode(img2,kernel1,iterations=1)
img2_erosion1 = cv2.erode(img2,kernel1,iterations=2)
img2_erosion2 = cv2.erode(img2,kernel1,iterations=3)
#膨胀
img_dilate = cv2.dilate(img2,kernel1,iterations=1)
img_dilate1 = cv2.dilate(img2,kernel1,iterations=2)
img_dilate2 = cv2.dilate(img2,kernel1,iterations=3)

res_erosion = np.hstack((img2_erosion,img2_erosion1,img2_erosion2))
res_dilate = np.hstack((img_dilate,img_dilate1,img_dilate2))\

cv2.imshow("DIGE",img1_erosion)
cv2.imshow("PIE",res_erosion)
cv2.imshow("PIE1",res_dilate)

cv2.waitKey(0)

cv2.destroyAllWindows()

实验结果

  腐蚀效果

        
                                        腐蚀图                                                  原图

  膨胀效果
                原图
            
                膨胀1,2,3次结果图