Design and implementation of a real-time LDWS with parameter space filtering for embedded platforms

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dc.authoridselim, erman/0000-0003-4479-0406
dc.authoridAlcı, Musa/0000-0002-5382-3460
dc.authorscopusid55899408300
dc.authorscopusid55899323700
dc.authorscopusid23393496100
dc.authorwosidselim, erman/ACZ-1332-2022
dc.authorwosidAlcı, Musa/ABI-3917-2020
dc.contributor.authorSelim, Erman
dc.contributor.authorAlci, Musa
dc.contributor.authorUgur, Aybars
dc.date.accessioned2023-01-12T19:50:58Z
dc.date.available2023-01-12T19:50:58Z
dc.date.issued2022
dc.departmentN/A/Departmenten_US
dc.description.abstractIn this work, a lane departure warning system (LDWS) algorithm for embedded platforms which has restricted resources is proposed. An LDWS consists of two main sub-functions which are lane detection and lane tracking. Although sophisticated methods have been developed for both sub-functions, they usually require high processing power and even GPU processing power. Therefore, they are not applicable for hardware with limited resources. In this work, Hough Transform (HT)-based lane detection algorithm is applied. The vulnerability of HT-based methods against misleading images is eliminated by the proposed filtering algorithm. Main differences of the proposed filtering algorithm from the classical methods in the literature are that it is applied in the parameter space rather than the image, and it is specialized only for determining lanes. In the lane tracking stage, the K-means clustering algorithm has been modified to operate online. In this way, the parameters of the detected lane can be followed adaptively during lane changing or overtaking. Real-time test results on embedded hardware demonstrated that the processing time does not exceed 41.67 ms with an accuracy of over 91.5%.en_US
dc.description.sponsorshipBMC Automotive Industry Company; Ministry of Science, Industry and Technology under the title of Lane Detection and Tracking System Design for Commercial Vehicles [01229.STZ.2012-1]en_US
dc.description.sponsorshipThis project was financially supported by the BMC Automotive Industry Company and Ministry of Science, Industry and Technology under the title of Lane Detection and Tracking System Design for Commercial Vehicles and grant order No. 01229.STZ.2012-1.en_US
dc.identifier.doi10.1007/s11554-022-01213-3
dc.identifier.endpage673en_US
dc.identifier.issn1861-8200
dc.identifier.issn1861-8219
dc.identifier.issn1861-8200en_US
dc.identifier.issn1861-8219en_US
dc.identifier.issue3en_US
dc.identifier.scopus2-s2.0-85127324880en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage663en_US
dc.identifier.urihttps://doi.org/10.1007/s11554-022-01213-3
dc.identifier.urihttps://hdl.handle.net/11454/76202
dc.identifier.volume19en_US
dc.identifier.wosWOS:000774843000001en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringer Heidelbergen_US
dc.relation.ispartofJournal Of Real-Time Image Processingen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectLane tracking systemen_US
dc.subjectReal-time applicationen_US
dc.subjectComputer visionen_US
dc.subjectHough transformen_US
dc.subjectParameter clusteringen_US
dc.subjectEmbedded system designen_US
dc.subjectRoad-Lane Detectionen_US
dc.subjectHough Transformen_US
dc.subjectVision Systemen_US
dc.titleDesign and implementation of a real-time LDWS with parameter space filtering for embedded platformsen_US
dc.typeArticleen_US

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