지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
이용수
초록· 키워드
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Corrosion detection and analysis is a very important topic in reducing costs and preventing disasters. Recently, image processing techniques have been widely applied to corrosion identification and analysis. In this work, we briefly introduces traditional image processing techniques and machine learning algorithms applied to detect or analyze corrosion in various fields. Recently, machine learning, especially CNN-based algorithms, have been widely applied to corrosion detection. Additionally, research on applying machine learning to region segmentation is very actively underway. The corrosion is reddish and brown in color and has a very irregular shape, so a combination of techniques that consider color and texture, various mathematical techniques, and machine learning algorithms are used to detect and analyze corrosion. We present examples of the application of traditional image processing techniques and machine learning to corrosion detection and analysis.
목차
Abstract
1. 서론
2. 컬러 모델
3. 영상처리 기법
4. 머신 러닝 기법
5. 예제
6. 결론
REFERENCES
참고문헌 (96)
참고문헌 신청
M. Komary, S. Komarizadehasl, N. Tooic, I. Segura, J.A. Lozano-Galant, J. Turmo, Low-cost technologies used in corrosion monitoring, Sensors, 23 (2023) 1309.
A. R. M. Forkan, Y. B. Kang, P. P. Jayaraman, K. Liao, R. Kaul, G. Morgan, S. Sinha, Corrdetector: A framework for structural corrosion detection from drone images using ensemble deep learning, Expert Systems with Applications, 193 (2022) 116461.
N. N. Almanza-Ortega, J. M. Flores-Vazquez, H. Martínez-Anorve, J. Perez-Ortega, J. C. Zavala-Diaz, A. Mexicano-Santoyo, J. C. Carmona-Fraustro, Corrosion analysis through an adaptive preprocessing strategy using the K-means algorithm, Procedia Computer S
M. A. Jayaram, M. A, Computer vision applications in construction material and structural health monitoring: A scoping review, Materials Today: Proceedings (2023) .
M. S. B. Reddy, D. Ponnamma, K. K. Sadasivuni, S. Aich, S. Kailasa, H. Parangusan, R. Zarandah, Sensors in advancing the capabilities of corrosion detection: A review, Sensors and Actuators A: Physical, 332 (2021) 113086.
A. R. M. Forkan, Y. B. Kang, P. P. Jayaraman, K. Liao, R. Kaul, G. Morgan, S. Sinha, Corrdetector: A framework for structural corrosion detection from drone images using ensemble deep learning, Expert Systems with Applications, 193 (2022) 116461.
N. N. Almanza-Ortega, J. M. Flores-Vazquez, H. Martínez-Anorve, J. Perez-Ortega, J. C. Zavala-Diaz, A. Mexicano-Santoyo, J. C. Carmona-Fraustro, Corrosion analysis through an adaptive preprocessing strategy using the K-means algorithm, Procedia Computer S
M. A. Jayaram, M. A, Computer vision applications in construction material and structural health monitoring: A scoping review, Materials Today: Proceedings (2023) .
M. S. B. Reddy, D. Ponnamma, K. K. Sadasivuni, S. Aich, S. Kailasa, H. Parangusan, R. Zarandah, Sensors in advancing the capabilities of corrosion detection: A review, Sensors and Actuators A: Physical, 332 (2021) 113086.
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