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首页> 外文期刊>Aerospace and Electronic Systems, IEEE Transactions on >Object-aware power line detection using color and near-infrared images
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Object-aware power line detection using color and near-infrared images

机译：使用彩色和近红外图像的对象感知电力线检测

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摘要

Vision-based power line detection (PLD) is an important yet challenging problem in low-altitude flight. Different from the traditional PLD methods, which only aim at line information, we propose a novel object-aware PLD method to obtain better detection performance. A new definition of power line is first proposed to present its object-aware properties; and then a cascaded PLD scheme is devised with line detection, region filtration, and object validation based on corresponding image cues in joint color (RGB) and near-infrared (NIR) images. Considering that the primary goal of PLD is to capture all potential information and decrease the false negatives, we first treat the universal line shape in pixel from joint RGB-NIR images as a basic feature to explore general line candidates. To further pick out the accurate regions occupied by power lines, on the one hand we filter the false candidates based on the region-based intensity of special material characteristics in NIR, and on the other hand we validate the power lines according to the color features in RGB. The experiments demonstrate the advantages of our proposed method in three aspects: good detection accuracy, high true detection rate, and low false detection rate.
机译：基于视觉的电力线检测（PLD）是低空飞行中一个重要但具有挑战性的问题。与仅针对行信息的传统PLD方法不同，我们提出了一种新颖的对象感知PLD方法，以获得更好的检测性能。首先提出一种新的电源线定义，以展示其对象感知特性。然后根据联合彩色（RGB）和近红外（NIR）图像中的相应图像提示，设计出具有线检测，区域过滤和对象验证的级联PLD方案。考虑到PLD的主要目标是捕获所有潜在信息并减少假阴性，因此我们首先将来自联合RGB-NIR图像的像素中的通用线条形状视为探索通用线条候选者的基本特征。为了进一步挑选出电源线所占据的准确区域，一方面，我们基于近红外光谱中特殊材料特征的基于区域的强度来过滤错误的候选对象，另一方面，我们根据颜色特征来验证电源线在RGB中。实验从三个方面证明了我们提出的方法的优点：良好的检测精度，较高的真实检测率和较低的错误检测率。

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