In this program, we will erode an image using the OpenCV function erode(). Erosion of image means to shrink the image. If any of the pixels in a kernel is 0, then all the pixels in the kernel are set to 0. One condition before applying an erosion function on image is that the image should be a grayscale image.
Original Image
Algorithm
Step 1: Import cv2 Step 2: Import numpy. Step 3: Read the image using imread(). Step 4: Define the kernel size using numpy ones. Step 5: Pass the image and kernel to the erode function. Step 6: Display the output.
Example Code
import cv2 import numpy as np image = cv2.imread('testimage.jpg') kernel = np.ones((7,7), np.uint8) image = cv2.erode(image, kernel) cv2.imshow('Eroded Image', image)