UAV Traffic Patrolling via Road Detection and Tracking in Anonymous Aerial Video Frames

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dc.authoridEREN, HALUK/0000-0002-4615-5783
dc.authoridKaraduman, Mucahit/0000-0002-8087-4044
dc.authorwosidCINAR, Ahmet/W-5792-2018
dc.authorwosidKaraduman, Mucahit/R-6853-2017
dc.contributor.authorKaraduman, Mucahit
dc.contributor.authorCinar, Ahmet
dc.contributor.authorEren, Haluk
dc.date.accessioned2024-08-04T20:45:40Z
dc.date.available2024-08-04T20:45:40Z
dc.date.issued2019
dc.departmentİnönü Üniversitesien_US
dc.description.abstractUnmanned Aerial Vehicles (UAV) have gained great importance for patrolling, exploration, and surveillance. In this study, we have estimated a route UAV to follow, using aerial road images. In the experimental setup, for estimation, test, and validation stages, anonymous aerial road videos have been exploited, meaning a special image database was not produced for this simulation approach. In the proposed study, road portion is initially detected. Two methods are utilized to help road detection, which are k-Nearest Neighbor and Hough transformation. To form a decision loop, both results are matched. If they match each other, they are fused using spatial and spectral schemes for the comparison purpose. Once road area is detected, the road type classification is realized by Fuzzy approach. The resultant image is utilized to estimate route, over which the UAV have to fly towards that direction. In the simulation stage, an anonymous video stream previously captured by UAV is experimented to assess the performance of the underlying system for different roads. According to the implementation results, the proposed algorithm has succeeded in finding all the trial roads in the given aerial images, and the proportion of all the estimated road-portion to actual road pixels for all the images is averagely calculated as %95.40. Eventually, it is shown that UAV has followed the correct route, which is estimated by proposed approach, over the specified road using assigned video frames, and also performances of spatial and spectral fusion results are compared.en_US
dc.identifier.doi10.1007/s10846-018-0954-x
dc.identifier.endpage690en_US
dc.identifier.issn0921-0296
dc.identifier.issn1573-0409
dc.identifier.issue2en_US
dc.identifier.scopus2-s2.0-85059591526en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage675en_US
dc.identifier.urihttps://doi.org/10.1007/s10846-018-0954-x
dc.identifier.urihttps://hdl.handle.net/11616/98599
dc.identifier.volume95en_US
dc.identifier.wosWOS:000476515600027en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofJournal of Intelligent & Robotic Systemsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectUAV reconnaissanceen_US
dc.subjectNextgen traffic patrollingen_US
dc.subjectAerial road trackingen_US
dc.subjectFuzzy classifieren_US
dc.subjectSpatial-spectral fusionen_US
dc.subjectRoute estimationen_US
dc.titleUAV Traffic Patrolling via Road Detection and Tracking in Anonymous Aerial Video Framesen_US
dc.typeArticleen_US

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