Improved fault detection for inline opticalinspections by evaluation of NIR images
Hartmut Eigenbrod
Kapitel/Beitrag aus dem Buch: Längle, T et al. 2013. OCM 2013 – Optical Characterization of Materials – conference proceedings.
Kapitel/Beitrag aus dem Buch: Längle, T et al. 2013. OCM 2013 – Optical Characterization of Materials – conference proceedings.
Industrial image processing is a widespread technology
to evaluate the quality of work pieces. Major advantages of
this technology are its contact-free mode of operation, fast evaluation
times and moderate system costs. Usually the visible part of
the light spectrum is used to discriminate between good and bad
work pieces. However, in several applications a combination or
even a substitution with the near infrared (NIR) part of the spectrum
advances the evaluation. In this paper, several real world
applications are presented and the achieved improvements are
summarized by showing qualitative and quantitative results.
1
Eigenbrod, H. 2013. Improved fault detection for inline opticalinspections by evaluation of NIR images. In: Längle, T et al (eds.), OCM 2013 – Optical Characterization of Materials – conference proceedings. Karlsruhe: KIT Scientific Publishing. DOI: https://doi.org/10.58895/ksp/1000032143-5
No license information is available about this publication.
Dieses Buch ist Peer reviewed. Informationen dazu Hier finden Sie mehr Informationen zur wissenschaftlichen Qualitätssicherung der MAP-Publikationen.
Veröffentlicht am 6. März 2013