edge-linking-using-hough-transform's Introduction

Edge-Linking-using-Hough-Transform

Aim:

To write a Python program to detect the lines using Hough Transform.

Software Required:

Anaconda - Python 3.7

Algorithm:

Step1:

Import the required modules.

Step2:

Import the image to operate on.

Step3:

Convert the imported image from BGR to GRAYSCALE.

Step4:

Find the edges using canny edge detector and display the image.

Step5:

Detect the points that form a line using hough transform.

Step6:

Draw the lines on the image

Step7:

Display the output

Step8:

End the program.

Program:


# Read image and convert it to grayscale image



import cv2
import matplotlib.pyplot as plt
import numpy as np
image = cv2.imread("suduko.webp")
grayImage = cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)
plt.imshow(grayImage)
cv2.imshow("Original Image",image)
cv2.imshow("Gray Image",grayImage)


# Find the edges in the image using canny detector and display


import cv2
import matplotlib.pyplot as plt
import numpy as np
image = cv2.imread("sudo.png")
grayImage = cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)
plt.imshow(grayImage,'gray')
cv2.imshow("Original Image",image)
cv2.imshow("Gray Image",grayImage)





# Detect points that form a line using HoughLinesP
lines = cv2.HoughLinesP(cannyEdges,1,np.pi/180,threshold=80,minLineLength = 50,maxLineGap = 250)


# Draw lines on the image
for line in lines:
x1, y1, x2, y2 = line [0]
cv2.line(image,(x1, y1),(x2, y2),(255, 0, 0),3)


# Display the result

plt.title("Hough Transform")
plt.imshow(image,'gray')
plt.show()