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Proceedings Paper

Determination of bake time and temperature of painted plastic using mathematical morphology and neural networks
Author(s): Robert M. Lougheed; Michelle Mikulec; John M. Trenkle; David L. McCubbrey
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Paper Abstract

This paper discusses a new automated image analysis technique for inspecting and monitoring changes in plastic bumper surfaces during the paint-baking process. This new technique produces excellent performance, and is appropriate for on-line production monitoring as well as laboratory analysis. The objective of this work was to develop an accurate method for determining the paint bake time and temperature at which parts had been treated. This task was accomplished using mathematical morphology to extract differentiating features from samples collected at three magnifications and sending these feature-vectors to a back-propagation neural network for classification.

Paper Details

Date Published: 18 September 1997
PDF: 11 pages
Proc. SPIE 3205, Machine Vision Applications, Architectures, and Systems Integration VI, (18 September 1997); doi: 10.1117/12.285584
Show Author Affiliations
Robert M. Lougheed, Environmental Research Institute of Michigan (United States)
Michelle Mikulec, Ford Motor Co. (United States)
John M. Trenkle, Environmental Research Institute of Michigan (United States)
David L. McCubbrey, Environmental Research Institute of Michigan (United States)


Published in SPIE Proceedings Vol. 3205:
Machine Vision Applications, Architectures, and Systems Integration VI
Susan Snell Solomon; Bruce G. Batchelor; John W. V. Miller, Editor(s)

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