The shapes of naturally occurring objects characteristically involve spatial events occurring at many scales. This paper offers a symbolic approach to constructing a primitive shape description across scales for 2D binary (silhouette) shape images: grouping operations are performed over collections of tokens residing on a Scale-Space Blackboard. Two types of grouping operations are identified that, respectively: (1) aggregate edge primitives at one scale into edge primitives at a coarser scale and (2) group edge primitives into partial-region assertions, including curved- contours, primitive-corners, and bars. This approach avoids several drawbacks of numerical smoothing methods.

This report shows how knowledge about the visual world can be built into a shape representation in the form of a descriptive vocabulary making explicit the important geometrical relationships comprising objects' shapes. Two computational tools are offered: (1) Shapestokens are placed on a Scale-Space Blackboard, (2) Dimensionality-reduction captures deformation classes in configurations of tokens. Knowledge lies in the token types and deformation classes tailored to the constraints and regularities ofparticular shape worlds. A hierarchical shape vocabulary has been implemented supporting several later visual tasks in the two-dimensional shape domain of the dorsal fins of fishes.