Indeed, segmentation is perhaps the central problem of artificial vision, and
accordingly many approaches have been proposed (for a nice survey of modern
segmentation methods, see the monograph [67]). There are basically two dual approaches.
In the first, one can start by considering the whole image to be the object
of interest, and then refine this initial guess. These “split and merge” techniques
can be thought of as somewhat analogous to the top-down processes of human
vision. In the other approach, one starts from one point assumed to be inside
the object, and adds other points until the region encompasses the object. Those
are the “region growing” techniques and bear some resemblance to the bottom-up
processes of biological vision.