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Open AccessJournal ArticleDOI

A Method Combining Line Detection and Semantic Segmentation for Power Line Extraction from Unmanned Aerial Vehicle Images

Wenbo Zhao, +2 more
- 11 Mar 2022 - 
- Vol. 14, Iss: 6, pp 1367-1367
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TLDR
This paper constructs a power line data set using UAV images and classify the data according to the image clutter and proposes a method combining line detection and semantic segmentation, which shows better performance on images with different IC.
Abstract
Power line extraction is the basic task of power line inspection with unmanned aerial vehicle (UAV) images. However, due to the complex backgrounds and limited characteristics, power line extraction from images is a difficult problem. In this paper, we construct a power line data set using UAV images and classify the data according to the image clutter (IC). A method combining line detection and semantic segmentation is used. This method is divided into three steps: First, a multi-scale LSD is used to determine power line candidate regions. Then, based on the object-based Markov random field (OMRF), a weighted region adjacency graph (WRAG) is constructed using the distance and angle information of line segments to capture the complex interaction between objects, which is introduced into the Gibbs joint distribution of the label field. Meanwhile, the Gaussian mixture model is utilized to form the likelihood function by taking the spectral and texture features. Finally, a Kalman filter (KF) and the least-squares method are used to realize power line pixel tracking and fitting. Experiments are carried out on test images in the data set. Compared with common power line extraction methods, the proposed algorithm shows better performance on images with different IC. This study can provide help and guidance for power line inspection.

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Citations
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Mission Chain Driven Unmanned Aerial Vehicle Swarms Cooperation for the Search and Rescue of Outdoor Injured Human Targets

TL;DR: In this paper , a cooperative strategy for distributed UAV swarms with different functions, namely the mission chain-driven unmanned aerial vehicle swarms cooperation method, is proposed to allow the fast search and timely rescue of injured human targets in a wide-area outdoor environment.
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Dual-View Stereovision-Guided Automatic Inspection System for Overhead Transmission Line Corridor

TL;DR: A novel UAV inspection system is developed, which can sense 3D information of transmission line corridor by the cooperation of the dual-view stereovision module and an advanced embedded NVIDIA platform, and an aerial image classification based on a light-weight semantic segmentation network to provide auxiliary information categories of ground objects.
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Distributed fixed-time time-varying formation-containment control for networked underactuated quadrotor UAVs with unknown disturbances

TL;DR: In this article , the fixed-time time-varying formation-containment (TVFC) control problem for multiple underactuated quadrotor unmanned aerial vehicles (QUAVs) with unknown disturbances is studied.
Journal ArticleDOI

Power Line Extraction Framework Based on Edge Structure and Scene Constraints

Kuansheng Zou, +1 more
- 13 Sep 2022 - 
TL;DR: In this article , a PLE method based on edge structure and scene constraints is proposed to solve the problem that small edge lines are extracted from scene images without power lines, and bringing about that power line extraction cannot be well applied in practice.
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Fast Detection of Defective Insulator Based on Improved YOLOv5s

TL;DR: In this paper , a new ResNet unit with three branches is designed based on depthwise separable convolution with kernel three and average pooling to reduce parameters and extract more useful features.
References
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Journal ArticleDOI

LSD: A Fast Line Segment Detector with a False Detection Control

TL;DR: A linear-time line segment detector that gives accurate results, a controlled number of false detections, and requires no parameter tuning is proposed.
Book

Markov Random Field Modeling in Computer Vision

TL;DR: This book presents a comprehensive study on the use of MRFs for solving computer vision problems, and covers the following parts essential to the subject: introduction to fundamental theories, formulations of MRF vision models, MRF parameter estimation, and optimization algorithms.
Journal ArticleDOI

Thermal and Narrowband Multispectral Remote Sensing for Vegetation Monitoring From an Unmanned Aerial Vehicle

TL;DR: The ability to generate quantitative remote sensing products by means of a helicopter-based UAV equipped with inexpensive thermal and narrowband multispectral imaging sensors is demonstrated, demonstrating comparable estimations, if not better, than those obtained by traditional manned airborne sensors.
Journal ArticleDOI

Automatic autonomous vision-based power line inspection: A review of current status and the potential role of deep learning

TL;DR: A new automatic autonomous vision-based power line inspection concept is proposed that uses Unmanned Aerial Vehicle (UAV) inspection as the main inspection method, optical images as the primary data source, and deep learning as the backbone of data analysis and inspection.
Journal ArticleDOI

Towards automatic power line detection for a UAV surveillance system using pulse coupled neural filter and an improved Hough transform

TL;DR: In this paper, a pulse coupled neural filter is developed to remove background noise and generate an edge map prior to the Hough transform being employed to detect straight lines, which is used by performing knowledge-based line clustering in Hough space to refine the detection results.
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