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All Journal MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology)
Muhammad Andik Izzudin
Faculty of Sains and Technology, UIN Sunan Ampel Surabaya
Computer Science & IT

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Eye Aspect Ratio based on Histogram Oriented Gradient and Linear Support Vector Machine to Microsleep Detection Mohammad Afinil Maula; Achmad Teguh Wibowo; Muhammad Andik Izzudin
MATICS: Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Vol 15, No 1 (2023): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/mat.v15i1.20186

Abstract

Traffic accidents are caused by several factors, especially due to driver fatigue. To minimize accidents caused by human negligence, developing a prototype microsleep detection system to trigger an alarm is necessary. This research uses Histogram Oriented Gradient and Support Vector Machine methods to detect objects. The programming language used is Python, using the dataset from the Idlib face landmark as a marker in the face point area, which will then be calculated based on the eye aspect ratio. This system is implemented using video input captured using a webcam in real-time. The output of this system uses a buzzer to alert the driver. In this study, the test results were obtained well, carried out with 2 test scenarios with a distance of 40cm - 100cm and testing light levels of 33 lux to 226 lux. From these results, the accuracy results were obtained at 88% each.
Eye Aspect Ratio based on Histogram Oriented Gradient and Linear Support Vector Machine to Microsleep Detection Mohammad Afinil Maula; Achmad Teguh Wibowo; Muhammad Andik Izzudin
MATICS: Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Vol 15, No 1 (2023): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/mat.v15i1.20186

Abstract

Traffic accidents are caused by several factors, especially due to driver fatigue. To minimize accidents caused by human negligence, developing a prototype microsleep detection system to trigger an alarm is necessary. This research uses Histogram Oriented Gradient and Support Vector Machine methods to detect objects. The programming language used is Python, using the dataset from the Idlib face landmark as a marker in the face point area, which will then be calculated based on the eye aspect ratio. This system is implemented using video input captured using a webcam in real-time. The output of this system uses a buzzer to alert the driver. In this study, the test results were obtained well, carried out with 2 test scenarios with a distance of 40cm - 100cm and testing light levels of 33 lux to 226 lux. From these results, the accuracy results were obtained at 88% each.
Co-Authors Achmad Teguh Wibowo Mohammad Afinil Maula