Experiments With Uas Imagery for Automatic Modeling of Power Line 3d Geometry

Jóźków, Grzegorz; Jagt, B. Vander; Toth, Charles K.

doi:10.5194/isprsarchives-xl-1-w4-403-2015

Cited by 13 publications

(9 citation statements)

References 9 publications

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“…We cannot directly compare the results to that of other studies because the system, the operation condition, and sites are different. But the result is decent that LiDAR systems show elevation accuracy within ±15 cm and previous studies on using aerial images reported the 3D power line extraction accuracy of 0.5 m referring to the ground truth data [15] and the fitting accuracy of 5–9 cm not using the ground truth [16]. …”

Section: Methodsmentioning

confidence: 99%

“…Zhang et al [15] used a fixed wing UAV for the power line inspection proposing a semi-patch matching algorithm based on an epipolar geometry of stereo images. They reported the experimental results of the elevation accuracy of 0.5 m. Jozkow et al [16] carried out the dense image matching for point cloud generation and filtering for the 3D modeling of power lines that they reported a fitting accuracy of 5–9 cm. These approaches follow the conventional image-to-object space approach that is comprised of line detection, image matching, and 3D reconstruction.…”

Section: Introductionmentioning

confidence: 99%

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3D Power Line Extraction from Multiple Aerial Images

Lee

2017

Sensors

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Power lines are cables that carry electrical power from a power plant to an electrical substation. They must be connected between the tower structures in such a way that ensures minimum tension and sufficient clearance from the ground. Power lines can stretch and sag with the changing weather, eventually exceeding the planned tolerances. The excessive sags can then cause serious accidents, while hindering the durability of the power lines. We used photogrammetric techniques with a low-cost drone to achieve efficient 3D mapping of power lines that are often difficult to approach. Unlike the conventional image-to-object space approach, we used the object-to-image space approach using cubic grid points. We processed four strips of aerial images to automatically extract the power line points in the object space. Experimental results showed that the approach could successfully extract the positions of the power line points for power line generation and sag measurement with the elevation accuracy of a few centimeters.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

3D Power Line Extraction from Multiple Aerial Images

Lee

2017

Sensors

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“…In previous research that used UAVs, it is possible to detect transmission lines under various conditions by using a convolutional neural network for UAV images [3]. In addition, the power line was sufficiently reconstructed by capturing the wire using approximately 10 pixels and reconstructing a three‐dimensional (3D) point cloud so that the position of the wire becomes clear [4]. However, in order to capture the power lines using such methods, it is necessary to capture data from a position close to the power lines, thereby increasing the risk of a UAV touching the power lines.…”

Section: Introductionmentioning

confidence: 99%

Time series analysis of separation for vegetation management around power lines using UAV photogrammetry

Arai

Kageyama

Ishizawa

et al. 2020

IEEJ Transactions Elec Engng

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In recent years, several studies have been performed on methods of investigating the periphery of power lines using remote sensing. Among the survey methods using unmanned aerial vehicles (UAVs), those methods are being studied wherein the environment around power lines is photographed by a UAV, and separation measurements are performed by reconstructing the three-dimensional (3D) point cloud between power lines and the vegetation. Such methods currently rely on reconstructing the power line, making it necessary to acquire images from a position close to the power line. However, by using information available from the power company on the position and structure of pylons and the sag of power lines, it is possible to calculate the position of the power line without 3D reconstruction. In this study, time series management of vegetation around power lines was enabled using the data obtained by UAVs at different times and information on the transmission equipment.

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“…There has been very little research on the 3D reconstruction of power lines from point clouds generated from multiple UAV images. The analysis of point clouds from UAV imagery for inspecting power lines was discussed for example in [14,15], where it was applied for detecting cable collision with terrain obstacles. Several researchers have proposed to increase the accuracy of extracting power lines from UAV images by improving the radiometry at the stage of preliminary image processing.…”

Section: Introductionmentioning

confidence: 99%

Improvement of 3D Power Line Extraction from Multiple Low-Cost UAV Imagery Using Wavelet Analysis

Fryśkowska

2019

Sensors

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Three-dimensional (3D) mapping of power lines is very important for power line inspection. Many remotely-sensed data products like light detection and ranging (LiDAR) have been already studied for power line surveys. More and more data are being obtained via photogrammetric measurements. This increases the need for the implementation of advanced processing techniques. In recent years, there have been several developments in visualisation techniques using UAV (unmanned aerial vehicle) platform photography. The most modern of such imaging systems have the ability to generate dense point clouds. However, image-based point cloud accuracy is very often various (unstable) and dependent on the radiometric quality of images and the efficiency of image processing algorithms. The main factor influencing the point cloud quality is noise. Such problems usually arise with data obtained via low-cost UAV platforms. Therefore, generated point clouds representing power lines are usually incomplete and noisy. To obtain a complete and accurate 3D model of power lines and towers, it is necessary to develop improved data processing algorithms. The experiment tested the algorithms on power lines with different voltages. This paper presents the wavelet-based method of processing data acquired with a low-cost UAV camera. The proposed, original method involves the application of algorithms for coarse filtration and precise filtering. In addition, a new way of calculating the recommended flight height was proposed. At the end, the accuracy assessment of this two-stage filtration process was examined. For this, point quality indices were proposed. The experimental results show that the proposed algorithm improves the quality of low-cost point clouds. The proposed methods improve the accuracy of determining the parameters of the lines by more than twice. About 10% of noise is reduced by using the wavelet-based approach.

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Experiments With Uas Imagery for Automatic Modeling of Power Line 3d Geometry

Cited by 13 publications

References 9 publications

3D Power Line Extraction from Multiple Aerial Images

3D Power Line Extraction from Multiple Aerial Images

Time series analysis of separation for vegetation management around power lines using UAV photogrammetry

Improvement of 3D Power Line Extraction from Multiple Low-Cost UAV Imagery Using Wavelet Analysis

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