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Proceedings Paper

Three-dimensional view planning for noncontact dimensional inspection
Author(s): Lester A. Gerhardt; Kwangik Hyun
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Paper Abstract

For dimensional inspection, the information on what to inspect usually is first obtained from the model. That will include geometric dimensions and tolerances (GD&Ts) as well as topological information about the model. Once items to be inspected are identified, the next step is inspection planning. Generally, there are several inspection features in one object. Using a vision system, we can see several features in one image. However, the features are not always inspectable because of the verification resolution (in other words, tolerance) constraint. To completely inspect the desired items (called 'inspection features'), one needs an algorithm for finding the optimum view sequence. In this paper, we discuss how to find the best view and optimum view sequence for inspection taking the desired verification resolution into consideration. To find the best view of an object, we use the number of inspectable features and verification resolution as parameters. We define the admissibility as an average resolution difference for every inspectable feature between the desired resolution and the calculated verification resolution in the selected image. Generally speaking, if a view has higher admissibility, the inspectable features in that view have a better verification resolution. Thus, if a view has more inspectable features, admissibility will be smaller. A feature visibility checking algorithm for view planning for 3-D optical image sensing is developed using a Z-buffer algorithm. Since the models used in this paper are approximated by triangular surfaces to obtain geometric and topological information from the CAD drawing, inputs for the algorithms are triangular surfaces. The result is output information about the number of visible surfaces and visible surface area with respect to a defined camera viewpoint. Both the theoretical development and practical application results are presented in this paper.

Paper Details

Date Published: 21 February 1996
PDF: 8 pages
Proc. SPIE 2665, Machine Vision Applications in Industrial Inspection IV, (21 February 1996); doi: 10.1117/12.232238
Show Author Affiliations
Lester A. Gerhardt, Rensselaer Polytechnic Institute (United States)
Kwangik Hyun, Rensselaer Polytechnic Institute (United States)

Published in SPIE Proceedings Vol. 2665:
Machine Vision Applications in Industrial Inspection IV
A. Ravishankar Rao; Ning Chang, Editor(s)

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