Abstract
Reliable detection of underground infrastructure is essential for infrastructure modernization works, the implementation of BIM technology, and 3D cadasters. This requires shortening the time of data interpretation and the automation of the stage of selecting the objects. The main factor that influences the quality of radargrams is noise. The paper presents the method of data filtration with use of wavelet analyses and Gabor filtration. The authors were inspired to conduct the research by the fact that the interpretation and analysis of radargrams is time-consuming and by the wish to improve the accuracy of selection of the true objects by inexperienced operators. The authors proposed automated methods for the detection and classification of hyperboles in GPR images, which include the data filtration, detection, and classification of objects. The proposed object classification methodology based on the analytic hierarchy process method introduces a classification coefficient that takes into account the weights of the proposed conditions and weights of the coefficients. The effectiveness and quality of detection and classification of objects in radargrams were assessed. The proposed methods make it possible to shorten the time of the detection of objects. The developed hyperbola classification coefficients show promising results of the detection and classification of objects.
Highlights
The detection of underground objects, in particular utility networks, is widely applied in civil engineering, geodesy, geology, and archaeology
The aim of our study is to automate and improve the accuracy of the process of detecting and classifying hyperbolas in ground penetrating radar (GPR) images using a proposed classification coefficient and two-stage approach
For the results obtained with Method 1, the following ranges (Q1 ) are proposed for the classification of objects detected in the radargram:
Summary
The detection of underground objects, in particular utility networks, is widely applied in civil engineering, geodesy, geology, and archaeology. One of the non-invasive geophysical methods for the detection of various underground media is the ground penetrating radar (GPR) method. The operation of such radar is based on the emission of electromagnetic waves that penetrate various geological media, followed by the reception of the beam reflected by the discontinuities of the structure of soil, rock, or material medium [1]. As a result of detection, the device operator obtains a set of radargrams that resemble the cross-section of soil in the given area. Radargrams are two-dimensional images that consist of numerous single signals reflected from soil media and recorded by the receiving antenna. The authors of publication [2] used the curvelet transform that is a development of the wavelet transform for the detection of pipes
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