Feature extraction is a term used with computers and machine learning. In conjunction with image processing, feature extraction begins with a set of measured data and then creates a series of derived values that are intended to informative and non-redundant. Related to dimensionality reduction, this process is intended to facilitate subsequent learning and generalization steps that can lead to better human interpretations. In short, dimensional data is entered into a computer to build a simulated 3-dimensional figure. From this simulation, humans can then manipulate these dimensions to create a desired form.