Feature extraction
Generally speaking, a feature is an interesting area of an image. It is a measurable property of an image that is very informative about what the image represents. Usually, the grayscale value of an individual pixel (the raw data) does not tell us a lot about the image as a whole. Instead, we need to derive a property that is more informative.
For example, knowing that there are patches in the image that look like eyes, a nose, and a mouth will allow us to reason about how likely it is that the image represents a face. In this case, the number of resources required to describe the data (are we seeing an image of a face?) is drastically reduced (does the image contain two eyes? a nose? a mouth?).
More low-level features, such as the presence of edges, corners, blobs, or ridges, may be more informative generally. Some features may be better than others, depending on the application. Once we have made up our mind on how to describe our favorite feature, we need to come up...
