edge-detection's Introduction

Edge-Detection

Aim:

To perform edge detection using Sobel, Laplacian, and Canny edge detectors.

Software Required:

Anaconda - Python 3.7

Algorithm:

Step1:

Import the required packages for further process.

Step2:

Read the image and convert the bgr image to gray scale image.

Step3:

Use any filters for smoothing the image to reduse the noise.

Step4:

Apply the respective filters -Sobel,Laplacian edge dectector and Canny edge dector.

Step5:

Display the filtered image using plot and imshow.

Program:

# Import the packages

import cv2
import numpy as np
import matplotlib.pyplot as plt

# Load the image, Convert to grayscale and remove noise


ip_img=cv2.imread("parrot.jpg")
gray_img=cv2.cvtColor(ip_img,cv2.COLOR_BGR2GRAY)
cv2.imshow("Canny edge detector",gray_img)
cv2.waitKey(0)
img=cv2.GaussianBlur(gray_img,(3,3),0)


# SOBEL EDGE DETECTOR

sobelx = cv2.Sobel(img,cv2.CV_64F,1,0,ksize=5)
sobely = cv2.Sobel(img,cv2.CV_64F,0,1,ksize=5)
sobelxy = cv2.Sobel(img,cv2.CV_64F,1,1,ksize=5)

plt.figure(1)
plt.subplot(2,2,1),plt.imshow(img,cmap = 'gray')
plt.title('Original'), plt.xticks([]), plt.yticks([])
plt.show()

plt.figure(1)
plt.subplot(2,2,1),plt.imshow(sobelx,cmap = 'gray')
plt.title('Sobelx'), plt.xticks([]), plt.yticks([])
plt.show()

plt.figure(1)
plt.subplot(2,2,1),plt.imshow(sobely,cmap = 'gray')
plt.title('Sobely'), plt.xticks([]), plt.yticks([])
plt.show()

plt.figure(1)
plt.subplot(2,2,1),plt.imshow(sobelxy,cmap = 'gray')
plt.title('Sobelxy'), plt.xticks([]), plt.yticks([])
plt.show()

# LAPLACIAN EDGE DETECTOR


laplacian = cv2.Laplacian(img,cv2.CV_64F)

cv2.imshow("Laplacian edge detector",laplacian)
cv2.waitKey(0)
cv2.destroyAllWindows()


# CANNY EDGE DETECTOR

canny = cv2.Canny(img1, 70, 150)
cv2.imshow("Canny edge detector",canny)
cv2.waitKey(0)
cv2.destroyAllWindows()