Python OpenCV | cv2.erode() 方法

OpenCV-Python是一个Python绑定库，旨在解决计算机视觉问题。 cv2.erode()方法用于对图像进行腐蚀。侵蚀的基本思想就像土壤侵蚀一样，它侵蚀了前景物体的边界（总是尽量保持前景为白色）。它通常在二进制图像上执行。它需要两个输入，一个是我们的原始图像，第二个称为结构元素或内核，它决定了操作的性质。只有当内核下的所有像素都为1时，原始图像中的一个像素（1或0）才会被认为是1，否则它会被侵蚀（变为0）。

Syntax: cv2.erode(src, kernel[, dst[, anchor[, iterations[, borderType[, borderValue]]]]])
Parameters:
src: It is the image which is to be eroded .
kernel: A structuring element used for erosion. If element = Mat(), a 3 x 3 rectangular structuring element is used. Kernel can be created using getStructuringElement.
dst: It is the output image of the same size and type as src.
anchor: It is a variable of type integer representing anchor point and it’s default value Point is (-1, -1) which means that the anchor is at the kernel center.
borderType: It depicts what kind of border to be added. It is defined by flags like cv2.BORDER_CONSTANT, cv2.BORDER_REFLECT, etc.
iterations: It is number of times erosion is applied.
borderValue: It is border value in case of a constant border.
Return Value: It returns an image.

用于以下所有示例的图像：

示例 #1：

# Python program to explain cv2.erode() method 
  
# importing cv2 
import cv2
  
# importing numpy 
import numpy as np
  
# path 
path = r'C:\Users\Rajnish\Desktop\geeksforgeeks\geeks.png'
  
# Reading an image in default mode 
image = cv2.imread(path) 
  
# Window name in which image is displayed 
window_name = 'Image'
  
# Creating kernel
kernel = np.ones((5, 5), np.uint8)
  
# Using cv2.erode() method 
image = cv2.erode(image, kernel) 
  
# Displaying the image 
cv2.imshow(window_name, image) 

输出：

示例 #2：

# Python program to explain cv2.erode() method 
  
# importing cv2 
import cv2
  
# importing numpy 
import numpy as np
  
# path 
path = r'C:\Users\Rajnish\Desktop\geeksforgeeks\geeks.png'
  
# Reading an image in default mode 
image = cv2.imread(path) 
  
# Window name in which image is displayed 
window_name = 'Image'
  
# Creating kernel
kernel = np.ones((6, 6), np.uint8)
  
# Using cv2.erode() method 
image = cv2.erode(image, kernel, cv2.BORDER_REFLECT) 
  
# Displaying the image 
cv2.imshow(window_name, image) 

输出：