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http://dx.doi.org/10.7582/GGE.2017.20.2.061

Application of Image Processing Techniques to GPR Data for the Reliability Improvement in Subsurface Void Analysis  

Kim, Bona (Department of Earth Resources and Environmental Engineering, Hanyang University)
Seol, Soon Jee (Department of Earth Resources and Environmental Engineering, Hanyang University)
Byun, Joongmoo (Department of Earth Resources and Environmental Engineering, Hanyang University)
Publication Information
Geophysics and Geophysical Exploration / v.20, no.2, 2017 , pp. 61-71 More about this Journal
Abstract
Recently, ground-penetrating radar (GPR) surveys have been actively carried out for precise subsurface void investigation because of the rapid increase of subsidence in urban areas. However, since the interpretation of GPR data was conducted based on the interpreter's subjective decision after applying only the basic data processing, it can result in reliability problems. In this research, to solve these problems, we analyzed the difference between the events generated from subsurface voids and those of strong diffraction sources such as the buried pipeline by applying the edge detection technique, which is one of image processing technologies. For the analysis, we applied the image processing technology to the GRP field data containing events generated from the cavity or buried pipeline. As a result, the main events by the subsurface void or diffraction source were effectively separated using the edge detection technique. In addition, since subsurface voids associated with the subsidence has a relatively wide scale, it is recorded as a gentle slope event unlike the event caused by the strong diffraction source recorded with a sharp slope. Therefore, the directional analysis of amplitude variation in the image enabled us to effectively separate the events by the subsurface void from those by the diffraction source. Interpretation based on these kinds of objective analysis can improve the reliability. Moreover, if suggested techniques are verified to various GPR field data sets, these approaches can contribute to semiautomatic interpretation of large amount of GPR data.
Keywords
GPR; Subsurface void; Image processing technique; Corner detection method;
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  • Reference
1 Cassidy, N. J., Eddies, R., and Dods, S., 2011, Void detection beneath reinforced concrete sections: The practical application of ground penetrating radar and ultrasonic techniques, Journal of Applied Geophysics, 74, 263-276.   DOI
2 Chen, J., 2009, The comparison and Application of Corner Detection Algorithms, Journal of Multimedia, 4, 435-441.
3 Collins, R., CSE 486 slides, Penn State University, http://www.cse.psu.edu/-rtc12/CSE486/ (January 23, 2017 Accessed)
4 Derpanis, K. G., 2004, The Harris Corner Detector, Technical Report, York University, http://www.cse.yorku.ca/-kosta/CompVis_Notes/harris_detector.pdf/ (January 23, 2017 Accessed).
5 GSSI (Geophysical Survey Systems, Inc.), http://www.geophysical.com/(January 23, 2017 Accessed).
6 Harris, C., and Stephens, M., 1988, A combined corner and edge detector, Proceedings of the 4th Alvey Vision Conference, 147-151.
7 Kang, Y. V., and Hsu, H., 2013, Application of Ground Penetrating Radar to Identify Shallow Cavities in a Coastal Dyke, Journal of Applied Science and Engineering, 16, 23-28.