Detecting edges

Edge detection is one of the most popular techniques in Computer Vision. It is used as a preprocessing step in many applications. Let's look at how to use different edge detectors to detect edges in the input image.

How to do it…

1. Create a new Python file, and import the following packages:

   import sys
   
   import cv2
   import numpy as np 

2. Load the input image. We will use chair.jpg:

   # Load the input image -- 'chair.jpg'
   # Convert it to grayscale 
   input_file = sys.argv[1]
   img = cv2.imread(input_file, cv2.IMREAD_GRAYSCALE)

3. Extract the height and width of the image:

   h, w = img.shape

4. Sobel filter is a type of edge detector that uses a 3x3 kernel to detect horizontal and vertical edges separately. You can learn more about it at http://www.tutorialspoint.com/dip/sobel_operator.htm. Let's start with the horizontal detector:

   sobel_horizontal = cv2.Sobel(img, cv2.CV_64F, 1, 0, ksize=5)

5. Run the vertical Sobel detector:

   sobel_vertical = cv2.Sobel(img, cv2.CV_64F, 0, 1, ksize=5)

6. Laplacian edge detector...