Existing bridges are critical components of transportation infrastruc- ture manly due to a huge volume of different corrosion. Corrosion reduced the performances of bridges and decrease their life services. Towards automatic de- tection of corrosion defects during inspections, a novel methodology is here pro- posed making use of machine vision concepts. Indeed, different types of corro- sion can be detected by image processing techniques that can be an appropriate tool also for the prediction of the damage evolution in bridges. Clustering K- means algorithms on image segmentation have been used to classify corrosion defect levels.
Detection of corrosion defects in steel bridges by machine vision / Kazemi, Majd. - (2021). (Intervento presentato al convegno EUROSTRUCT: International Conference of the European Association on Quality Control of Bridges and Structures tenutosi a University of Padova, Italy) [https://doi.org/10.1007/978-3-030-91877-4].
Detection of corrosion defects in steel bridges by machine vision
Kazemi MajdPrimo
Membro del Collaboration Group
2021
Abstract
Existing bridges are critical components of transportation infrastruc- ture manly due to a huge volume of different corrosion. Corrosion reduced the performances of bridges and decrease their life services. Towards automatic de- tection of corrosion defects during inspections, a novel methodology is here pro- posed making use of machine vision concepts. Indeed, different types of corro- sion can be detected by image processing techniques that can be an appropriate tool also for the prediction of the damage evolution in bridges. Clustering K- means algorithms on image segmentation have been used to classify corrosion defect levels.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
