Practical Computer Vision with SimpleCV

Chapter 7. Drawing on Images

Vision systems usually need to provide some form of feedback to its users. Although this could be in the form of messages printed to a log, a spreadsheet, or other data output, users are most comfortable with graphical output, in which key information is drawn directly on the image. This feedback is often more user-friendly because it is noticeable and can give the user more context about the message. When the program claims to have found features on an image, which ones did it find? Was it picking up noise? Is it finding the right objects? Even if the program will ultimately run without any user interaction, this type of feedback during development is vital. If, on the other hand, the system is designed to have users interacting with it, then drawing on images can be an important means for improving the user interface. For example, if the system measures several different objects, rather than printing a list of measurements to a console, it would be easier for the operator if the measurements were printed directly on the screen next to each object. This spares the operator from having to guess which measurements correspond to the different objects on the screen or trying to estimate which object is the correct one based on their coordinates.

The SimpleCV framework has a variety of methods for drawing on and marking up images. Some of these are standard tools, found in most basic image manipulation programs. These are functions like drawing boxes, circles, ...