So now that we’ve seen how to treat images as grids of pixels and as functions of x and y, let’s see how to use this information. We’ll start by learning how to use information about the colors in an image to isolate a particular area. This is an example of the computer vision pipeline step selecting areas of interest. This is easiest to understand in an example. We’ll be selecting an area of interest using a color threshold. Color thresholds are used in a number of applications including extensively in computer graphics and video. A common use is with a blue screen. A blue screen similar to a green screen is used to layer two images or video streams based on identifying and replacing a large blue area. We’re using a blue screen to film right now and the blue background can be replaced so that it looks like I’m in a different room, underwater- I’m swimming, or even in outer space. So, how does all this work? Well, the first step is to isolate the blue background and then replace that blue area with an image of your choosing. This task seems simple enough, so let’s see how to do this in code with our own image.