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Material classification through distance aware multispectral data fusion
Bonn-Rhein-Sieg University of Applied Sciences, St. Augustin, Germany. (Department of Computer Science)
Bonn-Rhein-Sieg University of Applied Sciences, St. Augustin, Germany. (Department of Computer Science)ORCID iD: 0000-0001-7776-2116
Bonn-Rhein-Sieg University of Applied Sciences, St. Augustin, Germany. (Department of Computer Science)
Bonn-Rhein-Sieg University of Applied Sciences, St. Augustin, Germany.
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2013 (English)In: Measurement science and technology, ISSN 0957-0233, E-ISSN 1361-6501, Vol. 24, no 4, article id 045001Article in journal (Refereed) Published
Abstract [en]

Safety applications require fast, precise and highly reliable sensors at low costs. This paperpresents signal processing methods for an active multispectral optical point sensorinstrumentation for which a first technical implementation exists. Due to the very demandingrequirements for safeguarding equipment, these processing methods are targeted to run on asmall embedded system with a guaranteed reaction time T < 2 ms and a sufficiently lowfailure rate according to applicable safety standards, e.g., ISO-13849. The proposed dataprocessing concept includes a novel technique for distance-aided fusion of multispectral datain order to compensate for displacement-related alteration of the measured signal. Thedistance measuring is based on triangulation with precise results even for low-resolutiondetectors, thus strengthening the practical applicability. Furthermore, standard components,such as support vector machines (SVMs), are used for reliable material classification. Allmethods have been evaluated for variants of the underlying sensor principle. Therefore, theresults of the evaluation are independent of any specific hardware.

Place, publisher, year, edition, pages
Bristol, United Kingdom: Institute of Physics (IOP), 2013. Vol. 24, no 4, article id 045001
Keywords [en]
Displacement measurement, optical sensor, optical triangulation, signal processing algorithm, detection and estimation, opto-electronic protective device
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-31085DOI: 10.1088/0957-0233/24/4/045001ISI: 000316452800002Scopus ID: 2-s2.0-84875399112OAI: oai:DiVA.org:oru-31085DiVA, id: diva2:653476
Available from: 2013-10-04 Created: 2013-10-04 Last updated: 2025-03-31Bibliographically approved

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Köckemann, Uwe

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