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Proceedings Paper

Perceptual feature-based object recognition for automatic inspection
Author(s): Gary P Brown; Peter Forte; Ron Malyan; Peter Barnwell
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Paper Abstract

This paper describes the development of a practical object recognition framework for industrial inspection applications. The framework is being used to develop a prototype automatic inspection system for Surface Mounted Electronic Assemblies. The recognition technique uses the object oriented paradigm to both process and model the image information. Three inter-linked information structures, that allow both image and object modelling information to be represented at multiple resolutions, are described in this paper. The first structure is a hierarchical feature based description constructed from the recursive grouping of perceptual features. The second structure provides a containment tree to describe the connections between sub-component parts of a complex object. The final structure is the inheritance tree that provides the capability to model multiple variations of the same object type. The inspection module begins by processing image information from a newly developed non-linear shape abstraction technique. The information is delivered in the form of a multi- resolution scale space description of the captured image.

Paper Details

Date Published: 6 August 1993
PDF: 12 pages
Proc. SPIE 2064, Machine Vision Applications, Architectures, and Systems Integration II, (6 August 1993); doi: 10.1117/12.150307
Show Author Affiliations
Gary P Brown, Mercury Communications Ltd. (United Kingdom)
Peter Forte, Kingston Univ. (United Kingdom)
Ron Malyan, Kingston Univ. (United Kingdom)
Peter Barnwell, Univ. of Plymouth (United Kingdom)


Published in SPIE Proceedings Vol. 2064:
Machine Vision Applications, Architectures, and Systems Integration II
Bruce G. Batchelor; Susan Snell Solomon; Frederick M. Waltz, Editor(s)

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