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Proceedings Paper

Show-and-go self-training qualitative package appearance inspection system
Author(s): Bruce E. Smyth
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Paper Abstract

In this paper we present a self-training high-speed inspection system which can be used in a variety of manufacturing applications for the detection of flaws in the overall appearance of products without requiring explicit specification of what defects are expected and in what regions. During training, the system is presented a number of good parts and learns and remembers two main aspects of a product: where edges are and where they are not. After showing the system a few images of the product, it expects areas of the product that had edge information to continue to have edge information and it expects `quite areas' to remain quiet. During run-time, if the system detects discrepancies in either category, it rejects the product. What sets this inspection system apart from traditional inspection machines is that it also has the ability to adapt to normal manufacturing realities. The system forgives changes in the product which occur during fabrication as long as they fall within an acceptable range. This range is defined by the manufacturing process itself during system training.

Paper Details

Date Published: 13 October 1994
PDF: 7 pages
Proc. SPIE 2354, Intelligent Robots and Computer Vision XIII: 3D Vision, Product Inspection, and Active Vision, (13 October 1994); doi: 10.1117/12.189082
Show Author Affiliations
Bruce E. Smyth, Acuity Imaging, Inc. (United States)


Published in SPIE Proceedings Vol. 2354:
Intelligent Robots and Computer Vision XIII: 3D Vision, Product Inspection, and Active Vision
David P. Casasent, Editor(s)

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