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Towards Surface Inference in Industrial Inspection : Technical Report IES-2016-04

Mohammadikaji, Mahsa

Abstract:
Automated product inspection play an important role in today’s manufacturing process, and therefore, the design of optimized and precise measurement setups are a requirement for efficient product quality assurance. Due to the high dimensionality of the design space, a manual choice of the geometrical and optical parameters is associated with high costs, tedious experimental work, and often non-optimal results. Thus, automatic planning methods which seek to optimize the setup degrees of freedom for a particular measurement are of special importance in this field. For automatic evaluation of an inspection, there exist typical evaluation metrics including but not limited to, the measurement uncertainty and the scan resolution. However, it is often not trivial how to combine different optimization criteria to optimize the setup based on the requirements. For example, it is not obvious how to compare an the result of an inspection with a high lateral resolution and a high uncertainty against another inspection, with a low lateral resolution but precise measurements. We propose to fuse the metrics through a probabilistic surface inference ... mehr


Zugehörige Institution(en) am KIT Institut für Anthropomatik und Robotik (IAR)
Publikationstyp Proceedingsbeitrag
Jahr 2017
Sprache Englisch
Identifikator ISBN: 978-3-7315-0678-2
ISSN: 1863-6489
URN: urn:nbn:de:swb:90-723502
KITopen ID: 1000072350
Erschienen in Proceedings of the 2016 Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics, Vision an Fusion Laboratory. Ed.: J. Beyerer
Verlag KIT Scientific Publishing, Karlsruhe
Seiten 43-57
Serie Karlsruher Schriften zur Anthropomatik / Lehrstuhl für Interaktive Echtzeitsysteme, Karlsruher Institut für Technologie ; Fraunhofer-Inst. für Optronik, Systemtechnik und Bildauswertung IOSB Karlsruhe ; 33
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