Recognition of horizontal layers in a segmented radargram after the application of Canny edge detector

This paper presents a method for the automated detection and elimination of horizontal reflections from ground penetrating radar (GPR) profiles after Canny edge filtering. Horizontal reflections are generated by interfaces between different media parallel to the air-soil interface. The recognition of horizontal layers is a crucial task when the number of layers and their thicknesses need to be estimated (e.g., in GPR road surveys). Identifying and deleting horizontal reflections from a radargram is also useful to facilitate the subsequent automated extraction of hyperbolic reflections [1-3]. It has to be noted that the removal of horizontal layers can increase the level of radargram segmentation.

In the proposed method, the first segmentation step is the application of Canny edge detector to the entire radargram. Then, horizontal layer recognition is done by carefully choosing boundary values. These values are varied many times until optimal values, depending on data acquisition parameters, are adopted. Special attention is paid to time efficiency of both segmentation steps, to investigate the possibility of employing the proposed solution in near real-time applications. The final result is an image where edge pixels arranged horizontally are removed.

Testing of this algorithm is done in MATLAB software environment, on a set of data with different levels of complexity, by varying the acquisition parameters.

References

[1]  A. Ristić, Ž. Bugarinović, M. Govedarica, L. Pajewski, and X. Derobert, “Verification of algorithm for point extraction from hyperbolic reflections in GPR data,” Proc. 9th International Workshop on Advanced Ground Penetrating Radar (IWAGPR 2017), Edinburgh, UK, pp. 1-5, 2017.

[2]  A. Ristić, M. Vrtunski, M. Govedarica, L. Pajewski, and X. Derobert, “Automated data extraction from synthetic and real radargrams of district heating pipelines,” Proc. 9th International Workshop on Advanced Ground Penetrating Radar (IWAGPR 2017), Edinburgh, UK, pp. 1-5, 2017.

[3]  Ž. Bugarinović, S.  Meschino, M. Vrtunski, L. Pajewski, A. Ristić, X. Derobert, and M. Govedarica, “Automated Data Extraction from Synthetic and Real Radargrams of Complex Structures,” Journal of Environmental and Engineering Geophysics, Vol. 23(4), pp. 407-421, 2018.