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Unmanned Aerial Patrol Technology Based on Tracking Algorithm of Target Tracking

机译:基于目标跟踪算法的无人机巡逻技术

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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.
机译:为了研究无人机的动力巡逻技术,采用了跟踪算法。根据算法讨论了电力线的自动巡逻。提出了一种基于机器视觉的无人机传输线检测方法。电力线无人飞行器检查的图像和视频背景复杂。通过维纳滤波降噪和概率密度函数,可以提高图像清晰度。根据现有的跟踪技术和算法,提出了一种基于无损卡尔曼滤波的凸轮轴目标跟踪算法。采用非破坏性卡尔曼滤波方法预测电力线识别的目标区域。使用凸轮轴算法,搜索窗口的预测并调整窗口的大小。传输线被实时跟踪。结果表明,该算法的恢复效果明显。图像的清晰度得到改善。它为提取和跟踪未来的传输线做好了准备。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种可行的方法。

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