Image processing may enhance condition assessment of bridge defects. In this perspective, we propose robotics and computer-aided procedure, which enables quantitative evaluation of defect extension with a specific storage organization, and performed by unmanned aerial vehicle (UAV). The methodology for defect evaluation uses color-based image processing. Data contained in digital images are taken on pre-classified structural elements. A campaign of UAV-based inspections has been performed to evidence the potentiality of the proposed procedure. Recurrent defects, occurring in infrastructure belonging to the Italian National railway system, allow evidencing the main features of the developed image-processing algorithm. The proposed process of damage detection and quantification is discussed with respect to both the level of automation that can be reached in each phase and the robustness of the used image processing adopted procedure.

A robotics and computer-aided procedure for defect evaluation in bridge inspection

Ottaviano E.
Formal Analysis
;
2020-01-01

Abstract

Image processing may enhance condition assessment of bridge defects. In this perspective, we propose robotics and computer-aided procedure, which enables quantitative evaluation of defect extension with a specific storage organization, and performed by unmanned aerial vehicle (UAV). The methodology for defect evaluation uses color-based image processing. Data contained in digital images are taken on pre-classified structural elements. A campaign of UAV-based inspections has been performed to evidence the potentiality of the proposed procedure. Recurrent defects, occurring in infrastructure belonging to the Italian National railway system, allow evidencing the main features of the developed image-processing algorithm. The proposed process of damage detection and quantification is discussed with respect to both the level of automation that can be reached in each phase and the robustness of the used image processing adopted procedure.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11580/81127
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