Durham School of Architectural Engineering and Construction


Date of this Version



Chongsheng Cheng, Ri Na, Zhigang Shen, Thermographic Laplacian-pyramid filtering to enhance delamination detection in concrete structure, Infrared Physics & Technology, Volume 97, 2019, Pages 162-176, ISSN 1350-4495, https://doi.org/10.1016/j.infrared.2018.12.039. (https://www.sciencedirect.com/science/article/pii/S1350449518307394)


© 2018 Published by Elsevier B.V. Used by permission.


Despite decades of efforts using thermography to detect delamination in concrete decks, challenges still exist in removing environmental noise from thermal images. The performance of conventional temperature-contrast approaches can be significantly limited by environment-induced non-uniform temperature distribution across imaging spaces. Time-series based methodologies were found robust to spatial temperature non-uniformity but requires extended period to collect data. A new empirical image filtering method is introduced in this paper to enhance the delamination detection using blob detection method that originated from computer vison. The proposed method employs a Laplacian of Gaussian filter to achieve multi-scale detection of abnormal thermal patterns by delaminated areas. Results were compared with the state-of-the-art methods and benchmarked with time-series methods in the case of handling non-uniform heat distribution issue. Tor further evaluate the performance of the method numerical simulations using transient heat transfer models were used to generate the ‘theoretical’ noise-free thermal images for comparison. Significant performance improvement was found compared to the conventional methods in both indoor and outdoor tests. This methodology proved to be capable to detect multi-size delamination using single thermal image. It is robust to non-uniform temperature distribution. The limitations were discussed to refine the applicability of the proposed procedure.