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Embedded Vision System for Automated Drone Landing Site Detection

机译:用于自动无人机着陆网站检测的嵌入式视觉系统

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This paper presents an embedded video subsystem used to classify the terrain, based on an image from a camera located under the drone, for the purpose of an automatic landing system. Colour and texture features, as well as decision trees and support vector machine classifiers were analysed and evaluated. The algorithm was supported with a shadow detection module. It was evaluated on 100 test cases and achieved over 80% performance. The designed video system was implemented on two embedded platforms - a Zynq SoC (System on Chip -Field Programmable Gate Array + ARM processor system) and a Jetson GPU (Graphic Processing Unit + ARM processor system). The performance achieved on both architectures is compared and discussed.
机译:本文介绍了一个嵌入式视频子系统,用于根据来自无人机下方的摄像机的图像来分类地形,以便自动着陆系统。分析和评估颜色和纹理特征,以及决策树和支持矢量机分类器。暗影检测模块支持算法。它在100个测试用例中进行了评估,并实现了超过80%的性能。设计的视频系统是在两个嵌入式平台上实现的 - 一个Zynq SoC(芯片 - 场可编程门阵列+ ARM处理器系统的系统)和Jetson GPU(图形处理单元+ ARM处理器系统)。比较和讨论了两个架构上实现的性能。

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