Computer vision based vehicle detection for toll collection system using embedded Linux

Abhijeet Suryatali, V. B. Dharmadhikari
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引用次数: 38

Abstract

Many highway toll collection systems have already been developed and are widely used in India. Some of these include Manual toll collection, RF tags, Barcodes, Number plate recognition. All these systems have disadvantages that lead to some errors in the corresponding system. This paper presents a brief review of toll collection systems present in India, their advantages and disadvantages and also aims to design and develop a new efficient toll collection system which will be a good low cost alternative among all other systems. The system is based on Computer Vision vehicle detection using OpenCV library in Embedded Linux platform. The system is designed using Embedded Linux development kit (Raspberry pi). In this system, a camera captures images of vehicles passing through toll booth thus a vehicle is detected through camera. Depending on the area occupied by the vehicle, classification of vehicles as light and heavy is done. Further this information is passed to the Raspberry pi which is having web server set up on it. When raspberry pi comes to know the vehicle, then it access the web server information and according to the type of the vehicle, appropriate toll is charged. This system can also made to count moving vehicles from pre-recorded videos or stored videos by using the same algorithm and procedure that we follow in this paper.
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基于计算机视觉的收费系统车辆检测
许多高速公路收费系统已经开发出来,并在印度广泛使用。其中包括人工收费,射频标签,条形码,车牌识别。这些系统都有缺点,导致相应的系统存在一些误差。本文简要介绍了印度目前的收费系统,其优点和缺点,并旨在设计和开发一种新的高效收费系统,这将是所有其他系统中一个很好的低成本替代方案。该系统是基于计算机视觉的车辆检测,在嵌入式Linux平台上使用OpenCV库。本系统采用嵌入式Linux开发工具(树莓派)进行设计。在该系统中,摄像机捕捉通过收费站的车辆图像,从而通过摄像机检测车辆。根据车辆占用的面积,将车辆分为轻型和重型。进一步,这些信息被传递给树莓派,树莓派上设置了web服务器。当树莓派来知道车辆,然后它访问web服务器信息,并根据车辆的类型,收取适当的通行费。该系统还可以使用与本文相同的算法和程序,从预录制的视频或存储的视频中对移动车辆进行计数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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