Power Line Extraction Framework Based on Edge Structure and Scene Constraints

Zou, Kuansheng; Jiang, Zhenbang

doi:10.3390/rs14184575

Cited by 6 publications

(4 citation statements)

References 41 publications

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“…This aligns with I5.0's importance on secure and controlled access to data and technology integration [111], confirming that sensitive information remains protected while still promoting collaboration and data sharing among authorized stakeholders. The work in [112] summarizes a model for better traceability and tamperproofing of remote sensing data changes. It aims to integrate blockchain technology with remote sensing data sharing to confirm decentralized, secure, and reliable data storage.…”

Section: Logistics and Distributionmentioning

confidence: 99%

Remote Sensing for Agriculture in the Era of Industry 5.0—A Survey

Victor,

Maddikunta,

Mary

et al. 2024

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Agriculture can be regarded as the backbone of human civilization. As technology evolved, the synergy between agriculture and remote sensing has brought about a paradigm shift, thereby entirely revolutionizing the traditional agricultural practices. Nevertheless, the adoption of remote sensing technologies in agriculture face various challenges in terms of limited spatial and temporal coverage, high cloud cover, low data quality and so on. Industry 5.0 marks a new era in the industrial revolution, where humans and machines collaborate closely, leveraging their distinct capabilities, thereby enhancing the decision making capabilities, sustainability and resilience. This paper provides a comprehensive survey on remote sensing technologies and related aspects in dealing with the various agricultural practices in the Industry 5.0 (I5.0) era. We also elaborately discuss the various applications pertaining to I5.0enabled remote sensing for agriculture. Finally, we discuss several challenges and issues related to the integration of I5.0 technologies in agricultural remote sensing. This comprehensive survey on remote sensing for agriculture in Industry 5.0 era offers valuable insights into the current state, challenges, and potential advancements in the integration of remote sensing technologies and Industry 5.0 principles in agriculture, thus paving the way for future research, development, and implementation strategies in this domain.

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Section: Logistics and Distributionmentioning

confidence: 99%

Remote Sensing for Agriculture in the Era of Industry 5.0—A Survey

Victor,

Maddikunta,

Mary

et al. 2024

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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“…They utilized the edge attention fusion module and a high pass block to extract semantic and spatial data to enhance the detection result along the boundaries. In [9] a approach based on the edge structure and scene constraints was proposed. In [10] an approach based on Generative Adversarial Networks (GANs) is described for segmenting power lines from aerial images.…”

Section: Related Workmentioning

confidence: 99%

Domain Adaptation in Power Line Segmentation: A New Synthetic Dataset

Kalitsios,

Mygdalis,

Pitas

2023

2023 IEEE International Conference on Image Processing (ICIP)

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Power line segmentation is a critical component of UAV intelligent inspection systems to ensure the safe and reliable operation of power grids. For challenging-to-label tasks like this, simulators can efficiently generate large amounts of labeled data. In this work, a large-scale annotated synthetic power lines dataset generated utilizing the unity game engine and the unity perception package 1 . To address domain shift between real and synthetic domain, input-level adaptation performed. Additionally, a new power line segmentation loss developed to mitigate the effects of unbalanced pixel distributions among power lines and background. Experiments demonstrate that our approach achieves state-of-the-art performance on power line segmentation task.

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“…The occurrence of a blackout can cause significant financial losses and, in extreme cases, a humanitarian disaster. Many authors [ 2 , 10 , 13 , 14 , 15 , 16 , 17 ] see the solution to this problem in the use of UAVs and broadly understood methods of visual inspection.…”

Section: Introductionmentioning

confidence: 99%

Detection of Power Line Insulators in Digital Images Based on the Transformed Colour Intensity Profiles

Tomaszewski

Gasz

Osuchowski

2023

Sensors

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Proper maintenance of the electricity infrastructure requires periodic condition inspections of power line insulators, which can be subjected to various damages such as burns or fractures. The article includes an introduction to the problem of insulator detection and a description of various currently used methods. Afterwards, the authors proposed a new method for the detection of the power line insulators in digital images by applying selected signal analysis and machine learning algorithms. The insulators detected in the images can be further assessed in depth. The data set used in the study consists of images acquired by an Unmanned Aerial Vehicle (UAV) during its overflight along a high-voltage line located on the outskirts of the city of Opole, Opolskie Voivodeship, Poland. In the digital images, the insulators were placed against different backgrounds, for example, sky, clouds, tree branches, elements of power infrastructure (wires, trusses), farmland, bushes, etc. The proposed method is based on colour intensity profile classification on digital images. Firstly, the set of points located on digital images of power line insulators is determined. Subsequently, those points are connected using lines that depict colour intensity profiles. These profiles were transformed using the Periodogram method or Welch method and then classified with Decision Tree, Random Forest or XGBoost algorithms. In the article, the authors described the computational experiments, the obtained results and possible directions for further research. In the best case, the proposed solution achieved satisfactory efficiency (F1 score = 0.99). Promising classification results indicate the possibility of the practical application of the presented method.

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Power Line Extraction Framework Based on Edge Structure and Scene Constraints

Cited by 6 publications

References 41 publications

Remote Sensing for Agriculture in the Era of Industry 5.0—A Survey

Remote Sensing for Agriculture in the Era of Industry 5.0—A Survey

Domain Adaptation in Power Line Segmentation: A New Synthetic Dataset

Detection of Power Line Insulators in Digital Images Based on the Transformed Colour Intensity Profiles

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