Unmanned Aerial Patrol Technology Based on Tracking Algorithm of Target Tracking

Yao Yao, Q. Quan, Hong-hui Zhang, Qiong Li
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Abstract

In order to study the power patrol technology of unmanned aerial vehicle, the tracking algorithm was applied. The automatic patrolling of power lines was discussed in terms of algorithms. An unmanned aerial vehicle transmission line inspection method based on machine vision was proposed. The image and video of the unmanned aerial vehicle inspection of the power line had a complex background. By Wiener filtering de-noising and probability density functions, the image clarity was improved. According to the existing tracking techniques and algorithms, a Camshaft target tracking algorithm based on lossless Kalman filter was proposed. The method of non-destructive Kalman filter was adopted to predict the region of interest of power line identification. Using the Camshaft algorithm, the prediction of the window was searched and the size of the window was adjusted. Transmission lines were tracked in real time. The results showed that the restoration effect of the algorithm was obvious. The clarity of the image was improved. It prepared for the extraction and tracking of the future transmission lines. Therefore, the proposed method provides a feasible way for the UAV power line inspection technology based on machine vision.
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基于目标跟踪算法的无人机巡逻技术
为了研究无人机动力巡逻技术,应用了跟踪算法。从算法的角度对电力线的自动巡检进行了探讨。提出了一种基于机器视觉的无人机传输线检测方法。无人机对电力线巡检的图像和视频具有复杂的背景。通过维纳滤波去噪和概率密度函数,提高了图像的清晰度。在现有跟踪技术和算法的基础上,提出了一种基于无损卡尔曼滤波的凸轮轴目标跟踪算法。采用无损卡尔曼滤波方法预测电力线识别的兴趣区域。利用凸轮轴算法对预测窗口进行搜索,并调整窗口的大小。输电线路被实时跟踪。结果表明,该算法的恢复效果明显。提高了图像的清晰度。它为提取和跟踪未来的输电线路做了准备。因此,该方法为基于机器视觉的无人机电力线检测技术提供了一条可行的途径。
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