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Image Processing for Drones Detection

机译:无人机检测的图像处理

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摘要

Presently, Drones Quadcopter has caused tremendous problems threatening the military security boundary and the area under Thai Army's surveillance. This article presents a conceptual framework for detecting and tracking unmanned aircraft by applying image processing. Study and analysis Compare advantages and disadvantages in order to develop and provide suitable equipment and tools Replacement of imported high-priced With limiting factors, namely distance, time, terrain And interference resistance The researchers used the camera USB 3.0 Cameras and Open Source Computer Vision (OpenCV) as a software development library on Linux operating systems to automatically record movies. In order to bring the image to analyze and distinguish the object classification by using Machine Learning through a sample of correct information and some incorrect information. Which when detecting, the installed device will calculate the coordinates detected, lock the target, track the movement Voice notification and report. The experiment was conducted by using Anova to test various factors affecting the detection, such as speed, light, color and size in 350 feet with the equipment we installed. The results of the experiment concluded that there was only a speed that had an effect at 22.65.
机译:目前,无人机四轴飞行器已经造成了巨大的问题,威胁着军事安全边界和泰国陆军监视下的地区。本文提出了一种通过应用图像处理来检测和跟踪无人机的概念框架。研究和分析比较优势和劣势,以便开发和提供合适的设备和工具替代进口高价产品具有距离,时间,地形和抗干扰性的限制因素研究人员使用了USB 3.0相机和开源计算机视觉( OpenCV)作为Linux操作系统上的软件开发库来自动录制电影。为了使图像能够通过使用机器学习通过正确信息和一些不正确信息的样本来分析和区分对象分类。当检测到时,已安装的设备将计算检测到的坐标,锁定目标,跟踪运动的语音通知并进行报告。通过使用Anova测试我们安装的设备在350英尺内的速度,光线,颜色和大小等影响检测的各种因素,进行了该实验。实验结果得出结论,只有一个速度才达到22.65。

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