{"title":"Real-time regional road sign detection and identification using Raspberry Pi","authors":"R. Tarun, B. P. Esther","doi":"10.1109/ICNWC57852.2023.10127370","DOIUrl":null,"url":null,"abstract":"In India, there often arises a situation where mobile mapping/navigation services doesn’t always show the updated routes to the destination with accounting of frequent regional changes, that for an emergency vehicle may lead up to a dangerous situation, this can be resolved by using real-time image processing system in complementary with mapping/navigation services to recognize the street name sign boards and display it to the driver. In this paper, an affordable regional road sign detection and identification system is developed which can be fitted in vehicles for driver awareness. EfficientDet-Lite model architecture and TensorFlow Lite API is used for object identification in real-time through implementing it into a Raspberry Pi 4b board. To assess the performance of the system, various test was undertaken and the result show 100% detection precision and an average precision over 78% has been achieved with low latency.","PeriodicalId":197525,"journal":{"name":"2023 International Conference on Networking and Communications (ICNWC)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on Networking and Communications (ICNWC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNWC57852.2023.10127370","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In India, there often arises a situation where mobile mapping/navigation services doesn’t always show the updated routes to the destination with accounting of frequent regional changes, that for an emergency vehicle may lead up to a dangerous situation, this can be resolved by using real-time image processing system in complementary with mapping/navigation services to recognize the street name sign boards and display it to the driver. In this paper, an affordable regional road sign detection and identification system is developed which can be fitted in vehicles for driver awareness. EfficientDet-Lite model architecture and TensorFlow Lite API is used for object identification in real-time through implementing it into a Raspberry Pi 4b board. To assess the performance of the system, various test was undertaken and the result show 100% detection precision and an average precision over 78% has been achieved with low latency.
在印度，经常出现这样的情况，即移动地图/导航服务并不总是显示到目的地的最新路线，并考虑到频繁的区域变化，对于紧急车辆可能导致危险的情况，这可以通过使用实时图像处理系统与地图/导航服务相补充来解决，以识别街道名称招牌并将其显示给驾驶员。本文开发了一种经济实惠的区域道路标志检测识别系统，该系统可以安装在车辆上，以提高驾驶员的感知能力。通过将其实现到Raspberry Pi 4b板上，使用了efficientdent -Lite模型架构和TensorFlow Lite API进行实时对象识别。为了评估系统的性能，进行了各种测试，结果表明，在低延迟的情况下，检测精度达到100%，平均精度超过78%。
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