Skip to content
Related Articles

Related Articles

Python | Detect corner of an image using OpenCV
  • Last Updated : 15 Oct, 2018

OpenCV (Open Source Computer Vision) is a computer vision library that contains various functions to perform operations on Images or videos. OpenCV library can be used to perform multiple operations on videos.

Let’s see how to detect the corner in the image.

cv2.goodFeaturesToTrack() method finds N strongest corners in the image by Shi-Tomasi method. Note that the image should be a grayscale image. Specify the number of corners you want to find and the quality level (which is a value between 0-1). It denotes the minimum quality of corner below which everyone is rejected. Then provide the minimum Euclidean distance between corners detected.

Syntax : cv2.goodFeaturesToTrack(image, maxCorners, qualityLevel, minDistance[, corners[, mask[, blockSize[, useHarrisDetector[, k]]]]])

Image before corner detection:






# import the required library
import numpy as np
import cv2
from matplotlib import pyplot as plt
  
  
# read the image
img = cv2.imread('corner1.png')
  
# convert image to gray scale image
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
  
# detect corners with the goodFeaturesToTrack function.
corners = cv2.goodFeaturesToTrack(gray, 27, 0.01, 10)
corners = np.int0(corners)
  
# we iterate through each corner, 
# making a circle at each point that we think is a corner.
for i in corners:
    x, y = i.ravel()
    cv2.circle(img, (x, y), 3, 255, -1)
  
plt.imshow(img), plt.show()

Image after corner detection –

 Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.  

To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course. And to begin with your Machine Learning Journey, join the Machine Learning – Basic Level Course

My Personal Notes arrow_drop_up
Recommended Articles
Page :