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Towards feature-based underground void detection with ground penetrating radar from within sewers using image processing

Delft, M. van (2019) Towards feature-based underground void detection with ground penetrating radar from within sewers using image processing.

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Abstract:Non-invasive inspection techniques become more important for the rehabilitation of underground utilities. This research focusses on in-sewer Ground Penetrating Radar (GPR) to detect voids behind the sewer walls. Detection of small voids facilitates for maintenance to avert collapsing sewers and roads as the result of the growing voids. The comparison between ground surface GPR (planar) and in-sewer GPR (cylindrical) , helps to give insight into the effects of both topologies on simulated GPR radargrams. Image processing techniques are used to extract void characteristics as features, which are used for feature selection and the calculation of the classification accuracy of voids. The resulting feature set proves to contain similar features and classification accuracies for both the planar and cylindrical topology. Hence, the closedoff cylindrical shape of the sewer does not pose an issue in the classification of voids behind the sewer wall using the extracted features. Therefore, based on the simulations, the in-sewer GPR proves to have potential in void detection. More research regarding the application and environment is necessary to determine the potential in real-life circumstances.
Item Type:Essay (Master)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:54 computer science, 56 civil engineering
Programme:Embedded Systems MSc (60331)
Link to this item:http://purl.utwente.nl/essays/79979
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