利用FPGA进行图像处理的自动驾驶汽车开发

2019 International Conference on Field-Programmable Technology (ICFPT) Pub Date : 2019-12-01 DOI:10.1109/ICFPT47387.2019.00090

Hamish Simmonds, Nicholas Carlisle, Xue Li, Fanglin Mu, D. Bailey

{"title":"利用FPGA进行图像处理的自动驾驶汽车开发","authors":"Hamish Simmonds, Nicholas Carlisle, Xue Li, Fanglin Mu, D. Bailey","doi":"10.1109/ICFPT47387.2019.00090","DOIUrl":null,"url":null,"abstract":"This project outlines the steps taken to implement an autonomously driving car. As software-based image processing can be very slow and consume a lot of power, the algorithms have been implemented on an FPGA. To reduce computation times and complexity, opportunities for simplifying the algorithms are explored. White line detection and saturation thresholding is explored for lane and object detection respectively.","PeriodicalId":241340,"journal":{"name":"2019 International Conference on Field-Programmable Technology (ICFPT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Autonomous Vehicle Development Using FPGA for Image Processing\",\"authors\":\"Hamish Simmonds, Nicholas Carlisle, Xue Li, Fanglin Mu, D. Bailey\",\"doi\":\"10.1109/ICFPT47387.2019.00090\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This project outlines the steps taken to implement an autonomously driving car. As software-based image processing can be very slow and consume a lot of power, the algorithms have been implemented on an FPGA. To reduce computation times and complexity, opportunities for simplifying the algorithms are explored. White line detection and saturation thresholding is explored for lane and object detection respectively.\",\"PeriodicalId\":241340,\"journal\":{\"name\":\"2019 International Conference on Field-Programmable Technology (ICFPT)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Field-Programmable Technology (ICFPT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICFPT47387.2019.00090\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Field-Programmable Technology (ICFPT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICFPT47387.2019.00090","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 3

摘要

这个项目概述了实现自动驾驶汽车所采取的步骤。由于基于软件的图像处理速度非常慢且功耗很大，因此该算法已在FPGA上实现。为了减少计算时间和复杂性，探索了简化算法的机会。研究了白线检测和饱和阈值检测分别用于车道检测和目标检测。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Autonomous Vehicle Development Using FPGA for Image Processing

This project outlines the steps taken to implement an autonomously driving car. As software-based image processing can be very slow and consume a lot of power, the algorithms have been implemented on an FPGA. To reduce computation times and complexity, opportunities for simplifying the algorithms are explored. White line detection and saturation thresholding is explored for lane and object detection respectively.

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

2019 International Conference on Field-Programmable Technology (ICFPT)

自引率

0.00%

发文量