OpenCV – Edge Detection
Edge Detection is an image processing technique to find boundaries of objects in the image.
In this tutorial, we shall learn to find edges of focused objects in an image using Canny Edge Detection Technique.
Syntax – cv2.Canny()
The syntax of OpenCV Canny Edge Detection function is
edges = cv2.Canny('/path/to/img', minVal, maxVal, apertureSize, L2gradient) where
| Parameter | Description |
| /path/to/img (Mandatory) | File Path of the image |
| minVal (Mandatory) | Minimum intensity gradient |
| maxVal (Mandatory) | Maximum intensity gradient |
| apertureSize (Optional) | |
| L2gradient (Optional) (Default Value : false) | If true, Canny() uses a much more computationally expensive equation to detect edges, which provides more accuracy at the cost of resources. |
Example 1 – OpenCV Edge Detection
In this example, we python.png (an RGB image) as a GREY scale image. Then Canny() function is used to detect edges for the image.
edge-detection.py
import cv2
img = cv2.imread('/home/img/python.png')
edges = cv2.Canny(img,100,200)
cv2.imshow("Edge Detected Image", edges)
cv2.waitKey(0) # waits until a key is pressed
cv2.destroyAllWindows() # destroys the window showing image Input Image
Output Image
Conclusion
In this OpenCV Python Tutorial – Image Edge Detection, we have learnt to find edges of objects in the specified image, using Canny Detection Algorithm.