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...