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Automated Stand-alone Video-based Microsleep Detection System by using EAR Technique

机译:基于EAR技术的自动独立式基于视频的微睡眠检测系统

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摘要

Microsleep while driving is the most event that contributes to the car accident. The proposed automated system deals with the development of system detection based on video of eye opening specifically for microsleep event among drivers. This system is used to help in avoidance of car accident that cause by microsleep among drivers while driving. Mainly, the objective of this proposed system is to detect the microsleep event while driving and to alert drivers because there is nobody can alert the driver with microsleep especially when they are driving alone. The proposed system is developed by using a python programming with image processing technique and Raspberry Pi module to make it applicable as stand-alone device. The EAR algorithm is the most importance in the proposed work as the microsleep detection made through eyes closure. Several conditions of eyes opening and closure, light and darkness, and with or without glasses/sunglasses have been tested. From the result, the proposed system shows that the ability of the proposed automated microsleep detection based on video imagery has showing a promising performance. However, the effectiveness of the eye detection must tolerate with the surrounding condition which also due to the type of camera used. Therefore, the camera is suggested to be able to function with night vision features such as infrared (IR) mode so it can be applied for daytime or night.
机译:驾驶时微睡是导致车祸的最主要因素。所提出的自动化系统涉及基于驾驶员睁眼视频的系统检测的开发,该视频专门针对驾驶员之间的微睡眠事件。该系统用于避免驾驶员在驾驶时因睡眠不足而引起的车祸。主要地,该提出的系统的目的是在驾驶时检测微睡眠事件并警告驾驶员,因为没有人可以用微睡眠来警告驾驶员,特别是当他们独自驾驶时。所提出的系统是通过使用具有图像处理技术的python编程和Raspberry Pi模块开发的,从而使其可作为独立设备使用。在建议的工作中,EAR算法是最重要的,因为通过闭眼进行微睡眠检测。已经测试了眼睛睁开和闭合,光线和黑暗以及有无眼镜/太阳镜的几种条件。从结果来看,所提出的系统表明,所提出的基于视频图像的自动微睡眠检测的能力已显示出令人鼓舞的性能。但是,眼睛检测的有效性必须能够承受周围环境的影响,这也取决于所用摄像机的类型。因此,建议该相机具有夜视功能,例如红外(IR)模式,因此可以在白天或晚上使用。

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