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Proceedings Paper

Reliable Object Acquisition Via Clustering Of Ambiguously Matching Features
Author(s): George C. Stockman
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Paper Abstract

Features which are easily extracted from an image are often at too low a level to be unambiguously matched to features of a model. However, if an elementary feature ei has some structure, only a limited number of transformations Tij can match it to similar model features mj. By extracting a set of features ei,i=l,...,n the transformation parameter space can be populated with a number of potential transformations Tij, i=1,...,n ; j=1,...,k. Clustering in this parameter space derives a transformation T that is supported by a large amount of local matching evidence. Simple clustering techniques are described for handling combined rotation and translation. Results are reported using the clustering technique with edge features and circular neighborhood features to acquire 2D objects.

Paper Details

Date Published: 22 November 1982
PDF: 7 pages
Proc. SPIE 0336, Robot Vision, (22 November 1982); doi: 10.1117/12.933614
Show Author Affiliations
George C. Stockman, The American University (United States)

Published in SPIE Proceedings Vol. 0336:
Robot Vision
Azriel Rosenfeld, Editor(s)

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