There are often many possible ways to solve a specific vision task. In some cases, the choice of either 2D or 3D vision is obvious, but in other cases both technologies could work though each provides certain benefits. It is important to understand these benefits and how they apply to a given application in order to provide a reliable machine vision solution. In general, 3D is best suited not only for analyzing volume, shape or 3D position of objects, but also for detecting parts and defects that are low contrast but have a detectable height difference. The third-dimension is mainly used for measuring, inspecting and positioning, but there are also cases where 3D is used to read imprinted code or text when contrast information is missing.
Capturing the third dimension can be done in many different ways, and each of the machine vision technologies available has its pros and cons. Three-dimensional imaging can be broken into two main categories: passive and active. From there it can be broken into much more specific techniques. Passive techniques include depth from focus, light field, and stereo. The main active techniques are based on time-of-flight, structured light, and interferometry.
Three-dimensional imaging can be further broken down into how the image is actually acquired, including snapshot and scanning methods.