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Anomaly detection in vehicle traffic with image processing and machine learning

Show simple item record Sarikan, S.S. Özbayoğlu, Ahmet Murat 2019-07-10T14:42:46Z 2019-07-10T14:42:46Z 2018
dc.identifier.citation Sarikan, S. S., & Ozbayoglu, A. M. (2018). Anomaly Detection in Vehicle Traffic with Image Processing and Machine Learning. Procedia Computer Science, 140, 64-69. en_US
dc.identifier.issn 18770509
dc.description Complex Adaptive Systems Conference with Theme: Cyber Physical Systems and Deep Learning (2018 : United States)
dc.description.abstract Anomaly detection is an important part of an Intelligent Transportation System. In this study, image processing and machine learning techniques are used to detect anomalies in vehicle movements. These anomalies include standing and traveling in reverse direction. Images are captured using CCTV cameras from front and rear side of the vehicle. This capability makes the results robust to the variations in operational and environmental conditions. Multiple consecutive frames are acquired for motion detection. Features such as edges and license plate corner locations are extracted for tracking purposes. Direction of the traffic flow is obtained from the trained classifier. K-nearest neighbor is chosen as the classifier model. The proposed method is evaluated on a public highway and promising detection results are achieved. © 2018 The Authors. Published by Elsevier B.V. en_US
dc.language.iso eng en_US
dc.publisher Elsevier B.V. en_US
dc.rights info:eu-repo/semantics/openAccess
dc.subject Vehicles en_US
dc.subject Classification (of information) en_US
dc.subject vehicle logo en_US
dc.title Anomaly detection in vehicle traffic with image processing and machine learning en_US
dc.type conferenceObject en_US
dc.relation.journal Procedia Computer Science en_US
dc.contributor.department TOBB ETU, Faculty of Engineering, Department of Computer Engineering en_US
dc.contributor.department TOBB ETÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü tr_TR
dc.identifier.volume 140
dc.identifier.startpage 64
dc.identifier.endpage 69
dc.identifier.scopus 2-s2.0-85061961476
dc.contributor.tobbetuauthor Özbayoğlu, Ahmet Murat
dc.contributor.YOKid 142991
dc.identifier.doi 10.1016/j.procs.2018.10.293
dc.contributor.wosresearcherID H-2328-2011
dc.contributor.ScopusAuthorID 6505999525
dc.relation.publicationcategory Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı tr_TR

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