Image-based crack identification for concrete bridges using region-based convolutional neural network

Research output: Chapter in Book/Report/Conference proceedingConference PaperOther

Abstract

Detecting concrete cracks is required in current condition assessment of bridges. In this study, a faster region-based convolutional neural network (faster R-CNN) was applied for image-based crack identification, where the real-world images taken from concrete bridges were contaminated with complex backgrounds including handwriting. For this purpose, dataset of 2489 cropped images was created and labelled for two different objects, i.e. cracks and handwriting. The proposed network was then trained and tested using the generated image dataset. Full-scale real-world images were then used to evaluate the performance of the trained network. The results of this study show that the faster R-CNN can locate crack automatically from raw images, even with the presence of handwriting scripts.

Original languageEnglish
Title of host publication9th International Conference on Structural Health Monitoring of Intelligent Infrastructure
Subtitle of host publicationTransferring Research into Practice, SHMII 2019 - Conference Proceedings
EditorsGenda Chen, Sreenivas Alampalli
PublisherInternational Society for Structural Health Monitoring of Intelligent Infrastructure, ISHMII
Pages524-529
Number of pages6
ISBN (Electronic)9780000000002
Publication statusPublished - 2019
EventInternational Conference on Structural Health Monitoring of Intelligent Infrastructure 2019 - St. Louis, United States of America
Duration: 4 Aug 20197 Aug 2019
Conference number: 9th
https://shmii-9.mst.edu/

Publication series

Name9th International Conference on Structural Health Monitoring of Intelligent Infrastructure: Transferring Research into Practice, SHMII 2019 - Conference Proceedings
Volume1

Conference

ConferenceInternational Conference on Structural Health Monitoring of Intelligent Infrastructure 2019
Abbreviated titleSHMII 2019
CountryUnited States of America
CitySt. Louis
Period4/08/197/08/19
Internet address

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