Evaluation of crack propagation in concrete bridges from vehicle-mounted camera images using deep learning and image processing

Autor: Yasutoshi Nomura, Masaya Inoue, Hitoshi Furuta
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Frontiers in Built Environment, Vol 8 (2022)
Druh dokumentu: article
ISSN: 2297-3362
DOI: 10.3389/fbuil.2022.972796
Popis: In Japan, all bridges should be inspected every 5 years. Usually, the inspection has been performed through the visual evaluation of experienced engineers. However, it requires a lot of load and expense. In order to reduce the inspection work, an attempt is made in this paper to develop a new inspection method using deep learning and image processing technologies. While using the photos obtained by vehicle-mounted camera, the damage states of bridges can be evaluated manually, it still requires a lot of time and load. To save the time and load, deep learning, which is a method of artificial intelligence is introduced. For image processing, it is necessary to utilize such pre-processing techniques as binarization of pictures and morphology treatment. To illustrate the applicability of the method developed here, some experiments are conducted by using the photos of running surface of concrete bridges of a monorail took by vehicle-mounted camera.
Databáze: Directory of Open Access Journals