Learning OpenCV, 2nd Edition

5

Filters and Convolution

Overview

At this point, we have all of the basics at our disposal. We understand the structure of the library as well as

the basic data structures it uses to represent images. We understand the HighGUI interface and can actually

run a program and display our results on the screen. Now that we understand these primitive methods

required to manipulate image structures, we are ready to learn some more sophisticated operations.

We will now move on to higher-level methods that treat the images as images, and not just as arrays of

colored (or grayscale) values. When we say “image processing,” we mean just that: using higher-level

operators that are defined on image structures in order to accomplish tasks whose meaning is naturally

defined in the context of graphical, visual images.

Before We Begin

There are a couple of important concepts we will need throughout this chapter, so it is worth taking a

moment to review these ideas before we dig into the specific image processing functions that make up the

bulk of this chapter. We will need to learn two main concepts: first, we’ll need to understand filters (also

called kernels) and how they are handled in OpenCV. Next, we’ll take a look at how boundaries are

handled, and what happens when OpenCV needs to compute something ...