{"title":"OpenCV based road sign recognition on Zynq","authors":"M. Russell, S. Fischaber","doi":"10.1109/INDIN.2013.6622951","DOIUrl":null,"url":null,"abstract":"Road sign recognition is a key component in autonomous vehicles and also has applications in driver assistance systems and road sign maintenance. Here an algorithm is presented using the Xilinx Zynq-7020 chip on a Zedboard to scan 1920×1080 images taken by an ON Semiconductor VITA-2000 sensor attached via the FMC slot. The PL section of the Zynq is used to perform essential image pre-processing functions and color based filtering of the image. Software classifies the shapes in the filtered image, and OpenCV's template matching function is used to identify the signs from a database of UK road signs. The system was designed in six weeks, and can process one frame in approximately 5 seconds. This is a promising start for a real-time System on Chip based approach to the problem of road sign recognition and also for using the Zynq platform for rapid deployment of these types of applications.","PeriodicalId":6312,"journal":{"name":"2013 11th IEEE International Conference on Industrial Informatics (INDIN)","volume":"1 1","pages":"596-601"},"PeriodicalIF":0.0000,"publicationDate":"2013-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"34","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 11th IEEE International Conference on Industrial Informatics (INDIN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INDIN.2013.6622951","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 34
Abstract
Road sign recognition is a key component in autonomous vehicles and also has applications in driver assistance systems and road sign maintenance. Here an algorithm is presented using the Xilinx Zynq-7020 chip on a Zedboard to scan 1920×1080 images taken by an ON Semiconductor VITA-2000 sensor attached via the FMC slot. The PL section of the Zynq is used to perform essential image pre-processing functions and color based filtering of the image. Software classifies the shapes in the filtered image, and OpenCV's template matching function is used to identify the signs from a database of UK road signs. The system was designed in six weeks, and can process one frame in approximately 5 seconds. This is a promising start for a real-time System on Chip based approach to the problem of road sign recognition and also for using the Zynq platform for rapid deployment of these types of applications.
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