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Proceedings Paper

Formalism for integrating machine vision systems: hierarchical token grouping
Author(s): Qian Huang
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Paper Abstract

While the view of constructive and hierarchial vision prevails, the issues of cooperation and competition among individual modules become crucial. These issues are directly related to one of the most important aspects in computer vision research: integration. A major source of difficulty in developing a consistent and systematic integration formalism is the heterogeneity existing in modules, in information, and in knowledge. In this paper, we exploit, using the central theme of grouping, the homogeneous characteristics in vision problem solving and propose a general framework, called Hierarchial Token Grouping, that facilitates vision problem solving by providing a consistent and systematic environment for integrating modules, cues, and knowledge, all in a globally coherent mechanism.

Paper Details

Date Published: 3 October 1994
PDF: 13 pages
Proc. SPIE 2347, Machine Vision Applications, Architectures, and Systems Integration III, (3 October 1994); doi: 10.1117/12.188725
Show Author Affiliations
Qian Huang, Michigan State Univ. (United States)

Published in SPIE Proceedings Vol. 2347:
Machine Vision Applications, Architectures, and Systems Integration III
Bruce G. Batchelor; Susan Snell Solomon; Frederick M. Waltz, Editor(s)

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