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首页> 外文期刊>International Journal of Modelling, Identification and Control >Front vehicle detection based on parallel Blob detection using quad-pipeline on FPGA
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Front vehicle detection based on parallel Blob detection using quad-pipeline on FPGA

机译:基于Parally Blob检测的前车辆检测在FPGA上使用四管道检测

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摘要

Real-time front vehicle detection is one of the important topics in intelligent transport systems. FPGA is an effective hardware device for high performance computing. This paper describes real-time front vehicle detection using quad-pipeline image processing on FPGA for intelligent transport systems. Front vehicle detection is implemented based on tail lights detection and white lines detection. When the two red Blobs of tail lights are detected between the two white line Blobs, the front vehicle is determined. For achieving real-time image processing on FPGA, the image is divided into four parts and the four image processing are realized by four-stage-pipeline. In detail, tail lights are detected using two pipelines, and white lines are detected using the other two pipelines. The experimental results show that the quad-pipeline system can detect a vehicle up ahead in 124.8 μ s on Artix7, which is 1.91 times faster than the dual-pipeline one.
机译:实时前车辆检测是智能传输系统中的重要主题之一。 FPGA是高性能计算的有效硬件设备。本文介绍了在FPGA上使用四管道图像处理的实时前车辆检测,用于智能传输系统。基于尾灯检测和白线检测来实现前车辆检测。当在两个白线灯之间检测到尾灯的两个红色斑点时,确定前车辆。为了实现对FPGA的实时图像处理,将图像分为四个部分,四级管道实现了四个图像处理。详细地,使用两个管道检测到尾灯,使用其他两个管道检测白线。实验结果表明,四管道系统可以在ARIX7上以124.8μs探测到124.8μs的车辆。比双管道速度快1.91倍。

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