Some convolution and scale transformation techniques to enhance GPR images
- Publication Type:
- Conference Proceeding
- Proceedings of the 14th IEEE Conference on Industrial Electronics and Applications, ICIEA 2019, 2019, pp. 1453 - 1458
- Issue Date:
Copyright Clearance Process
- Recently Added
- In Progress
- Open Access
This item is currently unavailable due to the publisher's embargo.
The embargo period expires on 16 Sep 2021
© 2019 IEEE. Locating reinforcement rods embedded inside concrete wall-like structures, as well as locating subsurface features such as voids, cracks, and interfaces is an essential part of structural health monitoring of concrete infrastructure. The Ground Penetrating Radar (GPR) technique has been commonly used as a means of Non-destructive Testing and Evaluation (NDT E) which suits the purpose. In the recent past, the interest of using GPR to assess the crowns (i.e., top) of concrete sewers has been rising. Moisture is well known to be a challenge for GPR imaging as moisture tends to influence GPR waves. This challenge becomes more common and persistent inside sewers since sewer walls contain considerable surface and subsurface moisture as a result of the humid environment created by the waste water flowing through sewers as well as the bacteria and gas induced acid attacks. Forming a part of sewer condition assessment-related research with the objective of assessing moist concrete, this paper presents some preliminary results which demonstrate how some simple scale transformations and convolution can help in enhancing GPR images in grey-scale. A set of raw GPR signals captured on a moist concrete block inside a laboratory environment is considered. The effect of enhancement is demonstrated against a benchmark image constructed by mapping the raw signals directly onto grey-scale.
Please use this identifier to cite or link to this item: