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Road condition analysis using NIR illumination and compensating for surrounding light
Lulea Univ Technol, Div Fluid & Expt Mech, S-97187 Lulea, Sweden.
Lulea Univ Technol, Div Fluid & Expt Mech, S-97187 Lulea, Sweden.
Luleå Univ Technol, Div Fluid & Expt Mech, S-97187 Luleå, Sweden.
Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
2016 (English)In: Optics and lasers in engineering, ISSN 0143-8166, E-ISSN 1873-0302, Vol. 77, 175-182 p.Article in journal (Refereed) Published
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Text
Abstract [en]

An investigation of a NIR camera system for road surface classification has been conducted for several road conditions. The surfaces were illuminated with three wavelengths, 980 nm, 1310 nm and 1550 nm and a halogen lamp, to simulate a real environment application with surrounding light. A measuring scheme to deal with surrounding light has been implemented enabling road condition classification from NIR images in a real environment. The retrieved camera images have been analyzed and an RGB representation of the different surfaces has been created to classify the different road conditions. The investigation shows that it is possible to distinguish between dry, moist, wet, frosty, icy and snowy road surfaces using a NIR camera system in a disturbed environment. (c) 2015 Elsevier Ltd. All rights reserved.

Place, publisher, year, edition, pages
2016. Vol. 77, 175-182 p.
Keyword [en]
Optics at surfaces, Infrared imaging, Hyperspectral imaging, Scattering measurements, Cameras
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:miun:diva-26869DOI: 10.1016/j.optlaseng.2015.08.002ISI: 000366617300021Scopus ID: 2-s2.0-84941908610Local ID: STCOAI: oai:DiVA.org:miun-26869DiVA: diva2:894739
Available from: 2016-01-15 Created: 2016-01-15 Last updated: 2017-06-29Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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  • Other style
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  • nn-NO
  • nn-NB
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Output format
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  • asciidoc
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