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Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Computer vision-based method for detecting cracks in reservoir dams
Reservoir dams serve as critical infrastructure. However, during their prolonged operation, cracks tend to appear on surfaces, particularly on slopes. The development of cracks poses risks to the stability of reservoir dams. This paper employs computer vision and deep learning methods to analyze images of reservoir dams. The primary directional characteristics of dam cracks are identified by leveraging deep learning method, and the distinctive features of cracks are calculated by utilizing the OpenCV platform and filtering techniques. Additionally, the fundamental features of cracks are determined through analysis and calculations using crack images of a dam as an example.
Computer vision-based method for detecting cracks in reservoir dams
Reservoir dams serve as critical infrastructure. However, during their prolonged operation, cracks tend to appear on surfaces, particularly on slopes. The development of cracks poses risks to the stability of reservoir dams. This paper employs computer vision and deep learning methods to analyze images of reservoir dams. The primary directional characteristics of dam cracks are identified by leveraging deep learning method, and the distinctive features of cracks are calculated by utilizing the OpenCV platform and filtering techniques. Additionally, the fundamental features of cracks are determined through analysis and calculations using crack images of a dam as an example.
Computer vision-based method for detecting cracks in reservoir dams
Nayyar, Anand (Herausgeber:in) / Kolivand, Hoshang (Herausgeber:in) / Qi, Bo (Autor:in) / Hou, Wenang (Autor:in)
Fourth International Conference on Signal Processing and Computer Science (SPCS 2023) ; 2023 ; Guilin, China
Proc. SPIE ; 12970
21.12.2023
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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