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An Assembled Detector Based on Geometrical Constraint for Power Component Recognition

1
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
2
School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China
3
Department of Geography, Pennsylvania State University, State College, PA 16801, USA
4
Shenzhen Power Supply Planning Design Institute Co., Ltd., Shenzhen 518054, China
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(16), 3517; https://doi.org/10.3390/s19163517 (registering DOI)
Received: 29 April 2019 / Revised: 30 July 2019 / Accepted: 8 August 2019 / Published: 11 August 2019
(This article belongs to the Special Issue UAV-Based Photogrammetry: Current Systems and Methods)
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Abstract

The intelligent inspection of power lines and other difficult-to-access structures and facilities has been greatly enhanced by the use of Unmanned Aerial Vehicles (UAVs), which allow inspection in a safe, efficient, and high-quality fashion. This paper analyzes the characteristics of a scene containing power equipment and the operation mode of UAVs. A low-cost virtual scene is created, and a training sample for the power-line components is generated quickly. Taking a vibration-damper as the main object, an assembled detector based on geometrical constraint (ADGC) is proposed and is used to analyze the virtual dataset. The geometric positional relationship is used as the constraint, and the Faster Region with Convolutional Neural Network (R-CNN), Deformable Part Model (DPM), and Haar cascade classifiers are combined, which allows the features of different classifiers, such as contour, shape, and texture to be fully used. By combining the characteristics of virtual data and real data using UAV images, the power components are detected by the ADGC. The result produced by the detector with relatively good performance can help expand the training set and achieve a better detection model. Moreover, this method can be smoothly transferred to other power-line facilities and other power-line scenarios. View Full-Text
Keywords: virtual image; vibration damper; assembled detector based on the geometrical constraint (ADGC); object detection; deep learning virtual image; vibration damper; assembled detector based on the geometrical constraint (ADGC); object detection; deep learning
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Ji, Z.; Liao, Y.; Zheng, L.; Wu, L.; Yu, M.; Feng, Y. An Assembled Detector Based on Geometrical Constraint for Power Component Recognition. Sensors 2019, 19, 3517.

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