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This has been called the linguistic or structural approach to the image recognition problem. R. Narasimhan [50, 51] proposes to compose images by using such elements as straight line segments or pieces of circular arcs. Each element has two or three distinguished points, to which the distinguished points of other elements are to be attached. The image of an arbitrary character can be formed in this way by the use of definite rules. The description of an input character image then consists of a list of its constituent elements and of a specification of the way in which they are interconnected.
V. P. Romanov  considers the problem of describing an image consisting of several nonintersecting black polygons. The elements he considers when analyzing the image are squares, each occupying a 7 x 7-cell portion of the retina. These squares are divided into 2, 4, or 8 sectors by lines radiating from the center of the square with an angular separation of 45° or a multiple of 45°. Some of the sectors are black, the rest white. The figures thus formed are used as templates for the analysis of the elements of images.
In this chapter we attempt to formulate the general problem in such a way as to include most of the particular problems of recognition and to let us regard them from a single point of view. Essentially, we propose an approach to the recognition problem that not only unites the earlier points of view but also sketches the way to overcome the difficulties encountered in earlier investigations. On the basis of this approach, a number of practical problems in recognition and learning have been solved.
Adobe(R) GoLive(R) 4.0 Classroom in a Book by Adobe Creative Team, Adobe Press