Opencv Corner Detection

This code utilizes OpenCV’s Fast algorithm to detect corners in an image, initializing the FAST object with default values and saving the results as ‘fast_true.png’ and ‘fast_false.png’. The Fast algorithm is a feature detection method that helps locate feature points or interest points in an image which can be useful for various computer vision tasks.

---

fast algorithm for corner detection

import numpy as np
import cv2 as cv
from matplotlib import pyplot as plt
img = cv.imread('blox.jpg',0) # `<opencv_root>/samples/data/blox.jpg`
# Initiate FAST object with default values
fast = cv.FastFeatureDetector_create()
# find and draw the keypoints
kp = fast.detect(img,None)
img2 = cv.drawKeypoints(img, kp, None, color=(255,0,0))
# Print all default params
print( "Threshold: {}".format(fast.getThreshold()) )
print( "nonmaxSuppression:{}".format(fast.getNonmaxSuppression()) )
print( "neighborhood: {}".format(fast.getType()) )
print( "Total Keypoints with nonmaxSuppression: {}".format(len(kp)) )
cv.imwrite('fast_true.png', img2)
# Disable nonmaxSuppression
fast.setNonmaxSuppression(0)
kp = fast.detect(img, None)
print( "Total Keypoints without nonmaxSuppression: {}".format(len(kp)) )
img3 = cv.drawKeypoints(img, kp, None, color=(255,0,0))
cv.imwrite('fast_false.png', img3)