This paper discusses image segmentation techniques from the standpoint of the assumptions that an image should satisfy in order for a particular technique to be applicable to it. These assumptions, which are often not stated explicitly, can be regarded as (perhaps informal) "models" for classes of images. The paper emphasizes two basic classes of models: statistical models that describe the pixel population in an image or region, and spatial models that describe the decomposition of an image into regions.