Abstract
Structural description of objects comprised descriptions of the parts and spatial relations between the parts. This paper presents a Hopfield net based scheme for matching structural shape descriptions. The current formulation of the matching scheme is general enough to take care of partial mismatch between the individual parts and spatial constraints between these parts. In addition, a transformation of the shape descriptions has been suggested with which shape descriptions containing asymmetrical spatial constraints between the parts can be matched using symmetric interconnection weights for the Hopfield net. The Hopfield net based formulation has been extended to consider the problem of finding the best match of the test shape descriptions with one of the stored prototypes. The matching scheme has been experimentally applied for recognition of hand-tools and symbols. In both cases, the network produced encouraging recognition results.
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