OpenCV Canny Edge Detection

by Online Tutorials Library July 14, 2022

OpenCV Canny Edge Detection

Edge detection is term where identify the boundary of object in image. We will learn about the edge detection using the canny edge detection technique. The syntax is canny edge detection function is given as:

Parameters-

/path/to/img: file path of the image (required)
minVal: Minimum intensity gradient (required)
maxVal: Maximum intensity gradient (required)
aperture: It is optional argument.
L2gradient: Its default value is false, if value is true, Canny () uses a more computationally expensive equation to detect edges, which provides more accuracy at the cost of resources.

Example: 1

  import cv2  img = cv2.imread(r’C:UsersDEVANSH SHARMAcat_16x9.jpg’)  edges = cv2.Canny(img, 100, 200)    cv2.imshow(“Edge Detected Image”, edges)  cv2.imshow(“Original Image”, img)  cv2.waitKey(0)  # waits until a key is pressed  cv2.destroyAllWindows()  # destroys the window showing image  

Output:

OpenCV Canny Edge detection

Example: Real Time Edge detection

  # import libraries of python OpenCV    import cv2    # import Numpy by alias name np  import numpy as np    # capture frames from a camera   cap = cv2.VideoCapture(0)    # loop runs if capturing has been initialized   while (1):        # reads frames from a camera       ret, frame = cap.read()        # converting BGR to HSV       hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)      # define range of red color in HSV       lower_red = np.array([30, 150, 50])      upper_red = np.array([255, 255, 180])        # create a red HSV colour boundary and        # threshold HSV image       mask = cv2.inRange(hsv, lower_red, upper_red)        # Bitwise-AND mask and original image       res = cv2.bitwise_and(frame, frame, mask=mask)        # Display an original image       cv2.imshow(‘Original’, frame)        # discovers edges in the input image image and       # marks them in the output map edges       edges = cv2.Canny(frame, 100, 200)        # Display edges in a frame       cv2.imshow(‘Edges’, edges)        # Wait for Esc key to stop       k = cv2.waitKey(5) & 0xFF      if k == 27:          break    # Close the window   cap.release()    # De-allocate any associated memory usage   cv2.destroyAllWindows()  

Output:

OpenCV Canny Edge detection

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Parameters-

Example: 1

Example: Real Time Edge detection

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