Hyperspectral imaging systems for corrosion detection from remotely operated vehicles

Thomas, Dominik; Gündel, Max

doi:10.1002/cepa.2132

“…By employing machine learning and feature extraction techniques, it achieves high accuracy in detecting cracks and complex objects on material surfaces, showcasing the potential of HSI for more effective and precise damage detection in built structures, surpassing traditional gray-valued images in performance. In [82], the authors propose the use of remotely operated vehicles equipped with HSI systems and machine learning algorithms to detect corrosion in steel infrastructure. HSI, offering both spatial and spectral information, proves valuable for material characterization and classification based on chemical properties in reflection spectra, offering a potential solution for efficient corrosion inspections in complex environments.…”

Section: E Industrial Manufacturing Management and Conservationmentioning

confidence: 99%

Hyperspectral Imaging Algorithms and Applications: A Review

Akewar,

Chandak

2023

Preprint

0

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<p>The paper covers topics ranging from hyperspectral imaging applications to innovative algorithms that have enhanced the analysis of hyperspectral data. We delve into the practical applications, including Agriculture, Food Quality and Safety, Earth Sciences, Exploration and Monitoring, Healthcare, Pharmaceuticals, Medical Imaging, Industrial Manufacturing, Management, Conservation, Safety and Security. Our goal is to provide a holistic understanding of how hyperspectral imaging is transforming these fields and driving new possibilities. We also discussed detailed algorithmic development in Hyperspectral Imaging including Supervised and Unsupervised algorithms. We reviewed algorithmic development from the early 1980’s to recent developments including Artificial Intelligence involving algorithms from Machine Learning to Deep Learning. We believe our paper will be of particular interest to your readers for those who wish to study algorithm development from simple image processing procedures to AI based approaches and how these algorithms are used in diverse applications to make intelligent decisions for increasing productivity and efficiency in Agriculture, Exploration and Management and identification of diseases and natural resources. Our paper is well organized into various sections as per algorithms and applications. We reviewed more than 250 papers with proper citations and authors' research work.</p>

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A Review of Emerging Sensor Technologies for Tank Inspection: A Focus on LiDAR and Hyperspectral Imaging and Their Automation and Deployment

Pallas Enguita,

Chen,

Kovacic

2024

Electronics

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This paper reviews various sensor technologies for tank inspection, focusing on Light Detection and Ranging (LiDAR) and Hyperspectral Imaging (HSI) as advanced solutions for corrosion detection. These technologies are evaluated alongside traditional methods such as ultrasonic, electromagnetic, and thermographic inspections. This review highlights their potential to enhance inspection accuracy, reduce the limitations of manual inspection, and support integrated data analysis for comprehensive asset management. Additionally, this paper proposes a pathway for automating these techniques to streamline inspection processes and improve implementation in practical applications.

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Hyperspectral Imaging Algorithms and Applications: A Review

Akewar,

Chandak

2023

Preprint

0

View full text Add to dashboard Cite

<p>The paper covers topics ranging from hyperspectral imaging applications to innovative algorithms that have enhanced the analysis of hyperspectral data. We delve into the practical applications, including Agriculture, Food Quality and Safety, Earth Sciences, Exploration and Monitoring, Healthcare, Pharmaceuticals, Medical Imaging, Industrial Manufacturing, Management, Conservation, Safety and Security. Our goal is to provide a holistic understanding of how hyperspectral imaging is transforming these fields and driving new possibilities. We also discussed detailed algorithmic development in Hyperspectral Imaging including Supervised and Unsupervised algorithms. We reviewed algorithmic development from the early 1980’s to recent developments including Artificial Intelligence involving algorithms from Machine Learning to Deep Learning. We believe our paper will be of particular interest to your readers for those who wish to study algorithm development from simple image processing procedures to AI based approaches and how these algorithms are used in diverse applications to make intelligent decisions for increasing productivity and efficiency in Agriculture, Exploration and Management and identification of diseases and natural resources. Our paper is well organized into various sections as per algorithms and applications. We reviewed more than 250 papers with proper citations and authors' research work.</p>

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Hyperspectral imaging systems for corrosion detection from remotely operated vehicles

Cited by 3 publications

References 13 publications

Hyperspectral Imaging Algorithms and Applications: A Review

Hyperspectral Imaging Algorithms and Applications: A Review

A Review of Emerging Sensor Technologies for Tank Inspection: A Focus on LiDAR and Hyperspectral Imaging and Their Automation and Deployment

Hyperspectral Imaging Algorithms and Applications: A Review

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