Driver fatigue detection with image processing

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dc.contributor.authorDuman, Mehmet
dc.contributor.authorErdogdu, Elifnaz
dc.contributor.authorCogen, Fatih
dc.contributor.authorYildiz, Tuba Conka
dc.date.accessioned2025-02-20T08:42:15Z
dc.date.available2025-02-20T08:42:15Z
dc.date.issued2020
dc.departmentTürk-Alman Üniversitesien_US
dc.description12th International Conference on Electrical and Electronics Engineering (ELECO) -- NOV 26-28, 2020 -- Bursa, TURKEYen_US
dc.description.abstractIn recent studies, drowsiness of drivers while driving is seen as one of the most important causes of deaths due to traffic accidents. Therefore, in this study, an algorithm that determines driver fatigue by examining the driver's eye conditions in real-time is proposed. Python versions of OpenCV (Open Source Computer Vision Library) and machine learning libraries were used to create this proposed algorithm. In the study, the face and eyes were detected with the Cascade classifier using Haar features. Detected eyes were classified as open closed or half open with the model trained by the SVM (Support Vector Machine) method according to the HOG (Histogram of Oriented Gradient) feature descriptor. Driver fatigue was decided according to the PERCLOS (Percentage of Eyelid Closure) method, which examines the percentage of eyelid closure over time. In the proposed system, fatigue was detected according to the time the driver's eyes were in the half-open or closed state, and a related user interface was designed and audio and visual warnings were given to the driver.
dc.identifier.doi10.1109/ELECO51834.2020.00049
dc.identifier.endpage250en_US
dc.identifier.isbn978-605-01-1331-0
dc.identifier.scopus2-s2.0-85100558338
dc.identifier.startpage246en_US
dc.identifier.urihttps://doi.org/10.1109/ELECO51834.2020.00049
dc.identifier.urihttps://hdl.handle.net/20.500.12846/1606
dc.identifier.wosWOS:000790328900050
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isotr
dc.publisherIEEE
dc.relation.ispartof2020 12th International Conference On Electrical and Electronics Engineering (Eleco)
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20250220
dc.titleDriver fatigue detection with image processing
dc.typeConference Object

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