Many algorithms for computer vision rely on locating interest points, or keypoints in each image, and calculating a feature description from the pixel region surrounding the interest point. This is in contrast to methods such as correlation, where a larger rectangular pattern is stepped over the image at pixel intervals and the correlation is measured at each location. The interest point is the anchor point and often provides the scale, rotational, and illumination invariance attributes for the descriptor; the descriptor adds more detail and more invariance attributes. Groups of interest points and descriptors together describe the actual objects.