基于图像的深度学习安全带牢度检测

Pub Date : 2022-12-24 DOI:10.12694/scpe.v23i4.2027
Rupal A. Kapdi, Pimal Khanpara, Rohan Modi, M. Gupta
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引用次数: 2

摘要

安全带的检测是车辆安全的一个重要方面。在发生事故时提供保护是至关重要的。许多汽车都安装了安全带检测装置,尽管它们可能很容易被操纵或忽视。因此,现有的安全带检测方法和算法存在不足。需要使用各种外部方法和算法来确定安全带是否系好。本文提出了一种利用图像处理和深度学习的概念来识别安全带牢度的方法。我们提出的方法可以在任何组织机构中部署,以帮助有关当局确定通过入口的车辆的司机是否系好安全带。如果在车辆中没有检测到安全带,车牌识别模块将记录车辆编号。有关当局可以利用这一记录采取进一步的必要行动。这样,组织当局可以跟踪所有进入场所的车辆,并确保所有驾驶员/副驾驶座位的乘客都系好安全带。
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Image-based Seat Belt Fastness Detection using Deep Learning
The detection of seat belts is an essential aspect of vehicle safety. It is crucial in providing protection in the event of an accident. Seat belt detection devices are installed into many automobiles, although they may be easily manipulated or disregarded. As a result, the existing approaches and algorithms for seat belt detection are insufficient. Using various external methods and algorithms, it is required to determine if the seat belt is fastened or not. This paper proposes an approach to identify seat belt fastness using the concepts of image processing and deep learning. Our proposed approach can be deployed in any organizational setup to aid the concerned authorities in identifying whether or not the drivers of the vehicles passing through the entrance have buckled their seat belts up. If a seat belt is not detected in a vehicle, the number plate recognition module records the vehicle number. The concerned authorities might use this record to take further necessary actions. This way, the organization authorities can keep track of all the vehicles entering the premises and ensure that all drivers/shotgun seat passengers are wearing seat belts.
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