The process of edge detection involves detecting sharp edges in the image and producing a binary image as the output. Typically, we draw white lines on a black background to indicate those edges. We can think of edge detection as a high pass filtering operation. A high pass filter allows high frequency content to pass through and blocks the low frequency content. As we discussed earlier, edges are high frequency content. In edge detection, we want to retain these edges and discard everything else. Hence, we should build a kernel that is the equivalent of a high pass filter.
Let's start with a simple edge detection filter known as the Sobel filter. Since edges can occur in both horizontal and vertical directions, the Sobel filter is composed of the following two kernels:
The kernel on the left detects horizontal edges and the kernel on the right detects vertical edges. OpenCV provides a function to directly apply the Sobel filter to a given image. Here is the code to use Sobel...
