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Proceedings Paper

Can Shape Description Be Applied To Model Matching?
Author(s): Richard Weiss
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Paper Abstract

One approach to object recognition is the -matching of two-dimensional contours, which are obtained from the projection of a three-dimensional model, with aggregates of lines extracted from an image. It is necessary to define geometric shape features which aid in the matching and can be used to compute a confidence measure for the match. Some of the standard features include curvature maxima and minima, points of inflection, trihedral vertices, and T-junctions. There has not been much evidence that global transforms such as Fourier series or symmetric axis transform make the solution any easier. What is needed is a hierarchical description which includes smooth curve segments and the types of junctions between them. A geometric grouping process is described which might be able to produce symbolic tokens in an image which could be matched hierarchically with a description from the model.

Paper Details

Date Published: 19 February 1988
PDF: 3 pages
Proc. SPIE 0848, Intelligent Robots and Computer Vision VI, (19 February 1988); doi: 10.1117/12.942743
Show Author Affiliations
Richard Weiss, University of Massachusetts (United States)


Published in SPIE Proceedings Vol. 0848:
Intelligent Robots and Computer Vision VI
David P. Casasent; Ernest L. Hall, Editor(s)

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