Introducing the Laplacian edge detector

The Laplacian edge detector uses only one kernel. It calculates second-order derivatives in a single pass and detects zero crossings. In general, the second-order derivative is extremely sensitive to noise.

The kernel for the Laplacian edge detector is shown in the following screenshot:

Fig 4.45: The Laplacian operator

The following is an example of gradient-based edge detection and Laplacian-based edge detection. We can see that the first-order derivative is calculated using gradient-based edge detection, and second-order derivatives are calculated using Laplacian edge detection: 

Fig 4.46: Gradient versus Laplacian edge detection

The objective of this book is to introduce you to the different edge detection concepts. If you want to read about these in more detail, you can go to https://en.wikipedia.org/wiki/Edge_detection.

In the next section, we will learn about an important concept called Canny edge detection.