在图形处理器上并行处理交通标志视频的算法

M. Umarov, Jamshid Elov, Sirojiddin Khalilov, Inomjon Narzullayev, Marat Karimov
{"title":"在图形处理器上并行处理交通标志视频的算法","authors":"M. Umarov, Jamshid Elov, Sirojiddin Khalilov, Inomjon Narzullayev, Marat Karimov","doi":"10.1109/ICISCT55600.2022.10146809","DOIUrl":null,"url":null,"abstract":"In the lighting conditions such as snowing, hazing, raining, and weak lighting condition, the accuracy of traffic sign recognition is not very high. It is important to develop an algorithms for real-time fast detection of road signs from video images and use them in driver assistance systems. Firstly, we image preprocessing by using dark channel prior based image dehazing for remove noises from the input image. In this article, we develop a transposed image filtering method combined with other fast parallel filtering algorithms. We propose a high-speed and high-accuracy method by improving image dehazing algorithms and analyzing GPU architecture. In this, we quickly removing fog from HD video images using DCP with image quality and visual effects.","PeriodicalId":332984,"journal":{"name":"2022 International Conference on Information Science and Communications Technologies (ICISCT)","volume":"14 3-4","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An algorithm for parallel processing of traffic signs video on a graphics processor\",\"authors\":\"M. Umarov, Jamshid Elov, Sirojiddin Khalilov, Inomjon Narzullayev, Marat Karimov\",\"doi\":\"10.1109/ICISCT55600.2022.10146809\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the lighting conditions such as snowing, hazing, raining, and weak lighting condition, the accuracy of traffic sign recognition is not very high. It is important to develop an algorithms for real-time fast detection of road signs from video images and use them in driver assistance systems. Firstly, we image preprocessing by using dark channel prior based image dehazing for remove noises from the input image. In this article, we develop a transposed image filtering method combined with other fast parallel filtering algorithms. We propose a high-speed and high-accuracy method by improving image dehazing algorithms and analyzing GPU architecture. In this, we quickly removing fog from HD video images using DCP with image quality and visual effects.\",\"PeriodicalId\":332984,\"journal\":{\"name\":\"2022 International Conference on Information Science and Communications Technologies (ICISCT)\",\"volume\":\"14 3-4\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-09-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 International Conference on Information Science and Communications Technologies (ICISCT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICISCT55600.2022.10146809\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Information Science and Communications Technologies (ICISCT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICISCT55600.2022.10146809","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

在下雪、雾霾、下雨、弱光等照明条件下,交通标志识别的准确率不是很高。开发一种从视频图像中实时快速检测道路标志并将其用于驾驶员辅助系统的算法非常重要。首先,采用基于暗通道先验的图像去雾方法对图像进行预处理,去除输入图像中的噪声。在本文中,我们开发了一种与其他快速并行滤波算法相结合的转置图像滤波方法。通过对图像去雾算法的改进和对GPU架构的分析,提出了一种高速、高精度的去雾方法。在此,我们使用具有图像质量和视觉效果的DCP快速去除高清视频图像中的雾。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An algorithm for parallel processing of traffic signs video on a graphics processor
In the lighting conditions such as snowing, hazing, raining, and weak lighting condition, the accuracy of traffic sign recognition is not very high. It is important to develop an algorithms for real-time fast detection of road signs from video images and use them in driver assistance systems. Firstly, we image preprocessing by using dark channel prior based image dehazing for remove noises from the input image. In this article, we develop a transposed image filtering method combined with other fast parallel filtering algorithms. We propose a high-speed and high-accuracy method by improving image dehazing algorithms and analyzing GPU architecture. In this, we quickly removing fog from HD video images using DCP with image quality and visual effects.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信