Next Article in Journal
Mango Leaf Monitoring with Inductive and Capacitive Sensors and Its Comparison with Trunk Dendrometer Measurements
Previous Article in Journal
Construction of an Observatory, As a Management Tool Decision, Valorisation and Sustainable Preservation of the Resources of Aromatic and Medicinal Plants
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Engineering Proceedings
Volume 8
Issue 1
10.3390/engproc2021008029
engproc-logo
Submit to this Journal
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Proceeding Paper

Defect Segmentation in Concrete Structures Combining Registered Infrared and Visible Images: A Comparative Experimental Study †

by
Sandra Pozzer
1,*,
Marcos Paulo Vieira de Souza
1,
Bata Hena
1,
Reza Khoshkbary Rezayiye
1,
Setayesh Hesam
1,
Fernando Lopez
2 and
Xavier Maldague
1
1
Department of Electrical and Computer Engineering, Laval University, 1065, Av., de la Médecine, Québec City, QC G1V 0A6, Canada
2
TORNGATS, Québec City, QC G2E 5V9, Canada
*
Author to whom correspondence should be addressed.
†
Presented at the 16th International Workshop on Advanced Infrared Technology & Applications, 26–28 October 2021; Available online: https://aita2021.sciforum.net/.
Eng. Proc. 2021, 8(1), 29; https://doi.org/10.3390/engproc2021008029
Published: 1 December 2021
(This article belongs to the Proceedings of The 16th International Workshop on Advanced Infrared Technology & Applications)
Browse Figure
Versions Notes

Abstract

This study investigates the semantic segmentation of common concrete defects when using different imaging modalities. One pre-trained Convolutional Neural Network (CNN) model was trained via transfer learning and tested to detect concrete defect indications, such as cracks, spalling, and internal voids. The model’s performance was compared using datasets of visible, thermal, and fused images. The data were collected from four different concrete structures and built using four infrared cameras that have different sensitivities and resolutions, with imaging campaigns conducted during autumn, summer, and winter periods. Although specific defects can be detected in monomodal images, the results demonstrate that a larger number of defect classes can be accurately detected using multimodal fused images with the same viewpoint and resolution of the single-sensor image.
Keywords: non-destructive testing; deep learning; image processing; multimodal images; infrared thermography; concrete bridges; infrastructure inspection non-destructive testing; deep learning; image processing; multimodal images; infrared thermography; concrete bridges; infrastructure inspection

Share and Cite

MDPI and ACS Style

Pozzer, S.; Souza, M.P.V.d.; Hena, B.; Rezayiye, R.K.; Hesam, S.; Lopez, F.; Maldague, X. Defect Segmentation in Concrete Structures Combining Registered Infrared and Visible Images: A Comparative Experimental Study. Eng. Proc. 2021, 8, 29. https://doi.org/10.3390/engproc2021008029

AMA Style

Pozzer S, Souza MPVd, Hena B, Rezayiye RK, Hesam S, Lopez F, Maldague X. Defect Segmentation in Concrete Structures Combining Registered Infrared and Visible Images: A Comparative Experimental Study. Engineering Proceedings. 2021; 8(1):29. https://doi.org/10.3390/engproc2021008029

Chicago/Turabian Style

Pozzer, Sandra, Marcos Paulo Vieira de Souza, Bata Hena, Reza Khoshkbary Rezayiye, Setayesh Hesam, Fernando Lopez, and Xavier Maldague. 2021. "Defect Segmentation in Concrete Structures Combining Registered Infrared and Visible Images: A Comparative Experimental Study" Engineering Proceedings 8, no. 1: 29. https://doi.org/10.3390/engproc2021008029

APA Style

Pozzer, S., Souza, M. P. V. d., Hena, B., Rezayiye, R. K., Hesam, S., Lopez, F., & Maldague, X. (2021). Defect Segmentation in Concrete Structures Combining Registered Infrared and Visible Images: A Comparative Experimental Study. Engineering Proceedings, 8(1), 29. https://doi.org/10.3390/engproc2021008029

Article Metrics

Back to TopTop