Eye Aspect Ratio based on Histogram Oriented Gradient and Linear Support Vector Machine to Microsleep Detection

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.