Point coordinates extraction from localized hyperbolic reflections in GPR data

Ristić, Aleksandar; Bugarinović, Željko; Vrtunski, Milan; Govedarica, Miro

doi:10.1016/j.jappgeo.2017.06.003

Cited by 21 publications

(12 citation statements)

References 23 publications

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“…Figure 10b shows a classic 2D view of the shaft where it is completely unclear how the pipelines in the shaft are organized. Figure 10c represents the 3D view of the shaft and gives a clear picture of the position of Based on georeferenced radargrams, photography, and relative measurements, this technology allows the user to transform on-site results into 2D or 3D models of underground utilities [28,29]. This is particularly important, since in the underground utility network, there are many examples of overlapping rights in 3D.…”

Section: Discussionmentioning

confidence: 99%

LADM Based Utility Network Cadastre in Serbia

Radulović

Sladić

Govedarica

et al. 2019

IJGI

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The utility network cadastre in Serbia is the main register of utility lines and the rights to them. The Law on State Survey and Cadastre states the necessity for implementing a unified information system of both a real estate and utility network cadastre, but this has not been achieved in practice. The reasons for such a unified information system are to ensure easier maintenance of the rights of both the utilities and properties located above or below them, to ensure more efficient procedures for obtaining the consent for placement, repair, or removal of the utility line, to prevent procedures being executed based on outdated data, to build an information system as the law prescribes, and to facilitate the business processes in the Serbian geodetic authority, since it is responsible for both registers. Therefore, an already-developed LADM (Land Administration Domain Model)-based country profile for Serbia should be extended to include information from the utility network cadastre. An analysis of Serbian legislation showed the necessity of extending the class set of the utility network cadastre by further specialization of the LADM LA_LegalSpaceUtilityNetwork class. Furthermore, such a system will support the maintenance of utility network data. In practice, when there is a change made on utility lines by the right holders, it is necessary to implement the change in the register. In many situations, this is not done, and the actual state does not correspond to the one in the register. Usually, modern technologies, such as ground penetrating radar (GPR) and LIDAR, are used for data acquisition in order to provide an update of the utility network data. Since these technologies produce 3D data, we analyzed how to link that data to the traditional 2D spatial paradigm.

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Section: Discussionmentioning

confidence: 99%

LADM Based Utility Network Cadastre in Serbia

Radulović

Sladić

Govedarica

et al. 2019

IJGI

Self Cite

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“…APEX (automated point extraction from radargrams) was recently developed with the primary objective of automatically detecting hyperbolic signatures in radargrams [14,[31][32][33].…”

Section: Automated Point Extraction From Radargrams (Apex) Algorithmmentioning

confidence: 99%

“…This parameter is used to constrain further searches: when the "sum of moves" exceeds a threshold, the search is stopped. The threshold does not have the same value for every radargram, and it mostly depends on the number of samples per scan: the bigger the number of samples per scan, the higher the value of the threshold [14]. It is possible that a SOI includes the right prong of hyperbolic reflection as well; thus, a second search is carried out where the starting pixel is between the second and third part of the SOI, instead of being between the first and second parts, and the search is conducted in the left segment of the radargram, with the starting pixel in the second row and second column of a 3 × 2 submatrix; the constraint is defined in the same manner as in the previously outlined case.…”

Section: Automated Point Extraction From Radargrams (Apex) Algorithmmentioning

confidence: 99%

“…The development of efficient, robust, and accurate algorithms capable of automatically finding hyperbolas in radargrams is currently a subject of high interest in the GPR scientific community [14], especially for real-field applications. To this aim, various supervised and unsupervised procedures have been proposed in the scientific literature; they make use of: Hough transform [15][16][17], radon transformation [18], wavelet transform [19], the Viola-Jones learning algorithm [20], or standard algorithms for pattern recognition, such as support vector machines [21][22][23] and artificial neural networks [24][25][26].…”

Section: Introductionmentioning

confidence: 99%

“…Another interesting approach is proposed and tested in [30]: the apices of well-and ill-shaped hyperbolas are automatically detected in radargrams by fitting an analytical function of a hyperbola to the profile edge dots detected with the Canny filter. The recently-proposed algorithm APEX (automated point extraction from radargrams) [14] is capable of finding the coordinates of hyperbola apices and extract the points on hyperbola prongs; it is based on the use of a cascade object detector (COD) to identify segments of interest that contain hyperbolic reflections and on a simple but smart procedure for the local search of apices. APEX has been successfully tested on synthetic data and experimental data recorded in complex urban environments during real GPR utility surveys [31][32][33].…”

Section: Introductionmentioning

confidence: 99%

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On the Introduction of Canny Operator in an Advanced Imaging Algorithm for Real-Time Detection of Hyperbolas in Ground-Penetrating Radar Data

et al. 2020

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This paper focuses on the use of the Canny edge detector as the first step of an advanced imaging algorithm for automated detection of hyperbolic reflections in ground-penetrating radar (GPR) data. Since the imaging algorithm aims to work in real time; particular attention is paid to its computational efficiency. Various alternative criteria are designed and examined, to fasten the procedure by eliminating unnecessary edge pixels from Canny-processed data, before such data go through the subsequent steps of the detection algorithm. The effectiveness and reliability of the proposed methodology are tested on a wide set of synthetic and experimental radargrams with promising results. The finite-difference time-domain simulator gprMax is used to generate synthetic radargrams for the tests, while the real radargrams come from GPR surveys carried out by the authors in urban areas. The imaging algorithm is implemented in MATLAB.

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Automatic detection of mud‐wall signatures in ground‐penetrating radar data

Bordón

Martinélli

Medina

et al. 2020

Archaeological Prospection

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The ground‐penetrating radar (GPR) method with the standard constant‐offset reflection mode allows to detect and map different types of archaeological structures, such as walls, foundations, floors and roads. The interpretation of the GPR data usually involves a detailed and time‐consuming analysis of large amounts of information, which entails nonnegligible chances of errors, especially under nonideal fieldwork conditions. The application of suitable automatic detection algorithms can be useful to more rapidly and successfully complete the interpretation task. In this work, we explore the use of supervised machine learning methodologies to automatically detect mud‐wall signatures in radargrams and to map the structures from these detections. Several algorithms, based on Viola–Jones cascade classifiers and the image feature descriptors Haar, histogram of oriented gradients and local binary patterns, were implemented. These algorithms were applied to datasets previously acquired in pre‐Inca and Inca‐Hispanic sites located in the Andean NW region of Argentina. The best algorithms provided very good detection rates for well‐preserved walls and acceptable rates for deteriorated walls, with a low number of spurious predictions. They also exhibited the ability to detect collapsed walls and fragments detached from them. These are remarkable results because mud walls are usually difficult to be detected by conventional analysis, owing to the complex and variable characteristics of their reflection patterns. The results of the automatic detection techniques were represented in plan views and three‐dimensional (3D) views that delineated in detail most of the structures of the sites. These algorithms are very fast, so applying them significantly reduces the interpretation times. In addition, once they have been trained using the patterns of one or several sites, they are directly applicable to other sites with similar characteristics.

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Point coordinates extraction from localized hyperbolic reflections in GPR data

Cited by 21 publications

References 23 publications

LADM Based Utility Network Cadastre in Serbia

LADM Based Utility Network Cadastre in Serbia

On the Introduction of Canny Operator in an Advanced Imaging Algorithm for Real-Time Detection of Hyperbolas in Ground-Penetrating Radar Data

Automatic detection of mud‐wall signatures in ground‐penetrating radar data

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