Morphological Transform 🔗

import albumentations as A
import cv2
from matplotlib import pyplot as plt

def visualize(image):
    plt.figure(figsize=(10, 5))
    plt.axis("off")
    plt.imshow(image)

Load the image from the disk

img_path = "../images/scan.jpeg"
img = cv2.imread(img_path, cv2.IMREAD_COLOR_RGB)

Visualize the original image 🔗

visualize(img)

png

Dilation expands the white (foreground) regions in a binary or grayscale image.

transform = A.Compose([A.Morphological(p=1, scale=(2, 3), operation="dilation")], p=1, seed=137, strict=True)

transformed = transform(image=img)
visualize(transformed["image"])

png

Erosion shrinks the white (foreground) regions in a binary or grayscale image.

transform = A.Compose([A.Morphological(p=1, scale=(2, 3), operation="erosion")], p=1, seed=137, strict=True)

transformed = transform(image=img)
visualize(transformed["image"])

png