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Machine vision approach for automating vegetation detection on railway tracks
Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.ORCID-id: 0000-0003-4812-4988
Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
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2013 (Engelska)Ingår i: Journal of Intelligent Systems, ISSN 2191-026X, Vol. 22, nr 2, s. 179-196Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

The presence of vegetation on railway tracks (amongst other issues) threatens track safety and longevity. However, vegetation inspections in Sweden (and elsewhere in the world) are currently being carried out manually. Manually inspecting vegetation is very slow and time consuming. Maintaining an even quality standard is also very difficult. A machine vision-based approach is therefore proposed to emulate the visual abilities of the human inspector. Work aimed at detecting vegetation on railway tracks has been split into two main phases. The first phase is aimed at detecting vegetation on the tracks using appropriate image analysis techniques. The second phase is aimed at detecting the rails in the image to determine the cover of vegetation that is present between the rails as opposed to vegetation present outside the rails. Results achieved in the current work indicate that the machine vision approach has performed reasonably well in detecting the presence/absence of vegetation on railway tracks when compared with a human operator.

Ort, förlag, år, upplaga, sidor
Walter de Gruyter, 2013. Vol. 22, nr 2, s. 179-196
Nationell ämneskategori
Annan elektroteknik och elektronik
Forskningsämne
Komplexa system - mikrodataanalys
Identifikatorer
URN: urn:nbn:se:du-12221DOI: 10.1515/jisys-2013-0017OAI: oai:DiVA.org:du-12221DiVA, id: diva2:621491
Tillgänglig från: 2013-05-15 Skapad: 2013-05-15 Senast uppdaterad: 2016-05-20Bibliografiskt granskad

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Nyberg, Roger G.

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Yella, SirilNyberg, Roger G.Dougherty, Mark
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