Perceptual organization for computer vision

Humans can easily group the elements in an image on such structural relationships as collinearity, parallelism, and symmetry. This phenomenon is called perceptual organization. To effectively use perceptual organization for computer vision, we require techniques for detecting such groupings in images, and techniques for utilizing the groupings for other stages of the visual process. In this work, we first detect edges in an image. We then group the edges based on the structural relationships among them. These groupings are treated as elements in the image, and are in turn grouped again. Thus, a hierarchy of such structural groupings is formed. The structural relationships used for the grouping are determined by the shapes of the objects being viewed. When the objects being viewed are known, we detect only those geometrical relationships which are found in those objects. To handle unknown objects, we detect the same geometrical relationships as the human visual system. We use the edge groupings to perform various visual tasks: for obtaining depth information stereooptically, for extracting from the image the objects being viewed, and for describing the shapes of the detected objects. (Copies available exclusively from Micrographics Department, Doheny Library, USC, Los Angeles, CA 90089-0182.)