使用更快R-CNN的车辆车牌自动检测

N.Palanivel Ap, T. Vigneshwaran, M.Sriv Arappradhan, R. Madhanraj
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引用次数: 9

摘要

本文的目的是识别车牌在困难的情况下,如扭曲,高/低光和多尘的情况下。本文提出利用Faster R-CNN从安装在交通区域等的监控摄像头中检测车辆车牌。所创建的系统用于捕获车辆的视频,然后使用帧分割和图像插值从视频中检测车牌,以获得更好的结果。从所得到的图像中,使用称为光学字符识别的技术对该图像进行数字识别。这些数字作为数据库的输入,用于检索车辆名称、车主姓名、地址、车主手机号码等数据。采用图形模型对系统的性能进行了测量。该系统检测车辆车牌并显示车主信息的准确率达到99.1%。
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Automatic Number Plate Detection in Vehicles using Faster R-CNN
The paper is aimed to identify the number plate in the vehicles during difficult situations like distorted, high/low light and dusty situations. The paper proposes the use of the Faster R-CNN to detect the number plate in the vehicle from the surveillance camera which is placed on the traffic areas etc. The created system is used to capture the video of the vehicle and then detect the number plate from the video using frame segmentation and image interpolation for better results. From the resulted image using the technique called optical character recognition is applied on that image for number recognition. These number are given as input to the database to retrieve data like vehicle's name, owner name, address, owner mobile number, etc. The performance of this system is measured using in a graph model. The proposed system is able to achieve a 99.1% accuracy to detect the number plate of the vehicle and show the vehicle's owner information.
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