Edge_Detection.py

#!/usr/bin/env python
# coding: utf-8

# In[1]:


import cv2
import numpy as np
import matplotlib.pyplot as plt
from scipy import ndimage

# Read the image
original_image = cv2.imread("cameraman.jpg")

# Convert the image to grayscale
gray_image = cv2.cvtColor(original_image, cv2.COLOR_BGR2GRAY)

# Apply the Canny edge detector
canny = cv2.Canny(gray_image, threshold1=30, threshold2=100)

# Apply the Laplacian edge detector
laplacian = cv2.Laplacian(gray_image, cv2.CV_64F, ksize=5)


# Compute Sobel gradients in both X and Y directions
sobel_x = cv2.Sobel(gray_image, cv2.CV_64F, 1, 0, ksize=3)
sobel_y = cv2.Sobel(gray_image, cv2.CV_64F, 0, 1, ksize=3)
# Combine the gradients to get the magnitude
sobel_magnitude = np.sqrt(sobel_x**2 + sobel_y**2)


# Initialize Roberts cross operator masks
roberts_cross_v = np.array([[1, 0], [0, -1]])
roberts_cross_h = np.array([[0, 1], [-1, 0]])
# Calculate vertical and horizontal gradients
vertical = ndimage.convolve(gray_image, roberts_cross_v)
horizontal = ndimage.convolve(gray_image, roberts_cross_h)
# Calculate gradient magnitude
roberts = np.sqrt(np.square(horizontal) + np.square(vertical))


# Display the original image, grayscale image, and edge-detected image
plt.figure(figsize=(15, 8))
plt.subplot(2, 4, 1)
plt.imshow(original_image, cmap="gray")
plt.title("Original Image")
plt.axis("off")

plt.subplot(2, 4, 2)
plt.imshow(gray_image, cmap="gray")
plt.title("Grayscale Image")
plt.axis("off")

plt.subplot(2, 4, 3)
plt.imshow(canny, cmap="gray")
plt.title("Canny Edge Detected Image")
plt.axis("off")

plt.subplot(2, 4, 4)
plt.imshow(laplacian, cmap="gray")
plt.title("Laplacian Edge Detected Image")
plt.axis("off")

plt.subplot(2, 4, 5)
plt.imshow(sobel_magnitude, cmap="gray")
plt.title("Sobel Edge Detected Image")
plt.axis("off")

plt.subplot(2, 4, 6)
plt.imshow(roberts, cmap="gray")
plt.title("Roberts Edge Detected Image")
plt.axis("off")

plt.subplot(2, 4, 7)
plt.imshow(canny)
plt.title("Image without cmap=gray")
plt.axis("off")

plt.subplot(2, 4, 8)
plt.imshow(original_image, cmap="gray")
plt.title("Image without axis=off")

plt.show()