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Proceedings Paper

Real-time defect detection using multiaperture fiber optic sensors and machine learning
Author(s): Hendrik Rothe; Angela Duparre; Peter Riedel; Monika Timm
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Paper Abstract

Smooth surfaces are widely applied in modern technology. Therefore a large variety of approaches for the determination of microtopographic surface descriptors has been developed. But there is a lack in adapted techniques for in-process surface assessment and defect detection. This paper deals with the development of an in-process sensor based on fiber optics and multivariate statistical signal processing.

Paper Details

Date Published: 17 December 1993
PDF: 12 pages
Proc. SPIE 1989, Computer Vision for Industry, (17 December 1993); doi: 10.1117/12.164860
Show Author Affiliations
Hendrik Rothe, Friedrich-Schiller-Univ. Jena (Germany)
Angela Duparre, Fraunhofer Institute for Applied Optics (Germany)
Peter Riedel, Friedrich-Schiller-Univ. Jena (Germany)
Monika Timm, Friedrich-Schiller-Univ. Jena (Germany)


Published in SPIE Proceedings Vol. 1989:
Computer Vision for Industry
Donald W. Braggins, Editor(s)

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