Real-time defect detection using multiaperture fiber optic sensors and machine learning

Hendrik Rothe; Angela Duparre; Peter Riedel; Monika Timm

doi:10.1117/12.164860

17 December 1993 Real-time defect detection using multiaperture fiber optic sensors and machine learning

Hendrik Rothe, Angela Duparre, Peter Riedel, Monika Timm

Proceedings Volume 1989, Computer Vision for Industry; (1993) https://doi.org/10.1117/12.164860
Event: Electronic Imaging Device Engineering, 1993, Munich, Germany

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.

Citation Download Citation

Hendrik Rothe, Angela Duparre, Peter Riedel, and Monika Timm "Real-time defect detection using multiaperture fiber optic sensors and machine learning", Proc. SPIE 1989, Computer Vision for Industry, (17 December 1993); https://doi.org/10.1117/12.164860

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