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

Bugarinović, Željko; Pajewski, Lara; Ristić, Aleksandar; Vrtunski, Milan; Govedarica, Miro; Borisov, Mirko

doi:10.3390/electronics9030541

Cited by 17 publications

(15 citation statements)

References 48 publications

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“…where a and c are the vector form of ail and cpm in (8), respectively. a and c are both N M   column vector, and they represent the unknown expansion coefficients in (2) and 3…”

Section: B Imaging Framework Based On T-matrix Methodsmentioning

confidence: 99%

“…Substituting (2) and (4) into the above two formulas, and using (5) to calculate the magnetic field component, the following two formulas are obtained.  from 0 to 2π on both sides of (A3) and (A4) simultaneously, which can remove all alternating components, and then we can get…”

Section: Appendixmentioning

confidence: 99%

“…Electromagnetic inverse scattering is dedicated to reconstructing the characteristics of the object from the measured scattered field data. It has a wide range of applications in biomedical imaging, ground-penetrating radar, non-destructive testing, through-the-wall imaging, and so forth [1][2][3][4]. As a typical inverse problem, electromagnetic inverse scattering has two major characteristics: nonlinearity and ill-posedness [5].…”

Section: Introductionmentioning

confidence: 99%

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A Fast Inverse Scattering Imaging Method by Applying Virtual Experiments to T-Matrix Scheme

et al. 2020

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As a non-iterative linear inverse scattering imaging method, the linear sampling method (LSM) has the merits of easy implementation and high computational efficiency. In this article, based on the LSM and T-matrix method, we propose a fast method to reconstruct the target medium parameters. First, we use the LSM qualitative imaging method to estimate the contour of the target. Then, the preprocessing information of the LSM is applied to the virtual experiment circles in the framework of T-matrix method. In this way, we avoid the inversion of the matrix and only need to solve a series of univariate equations. Numerical simulation results show that the reconstruction accuracy of the proposed method is similar to that of LSM quantitative imaging method, but it has higher calculation accuracy and wider application range. Although the calculation accuracy is not as good as the contrast source inversion (CSI) method, the proposed method has huge advantages in terms of calculation efficiency. INDEX TERMS Electromagnetic inverse scattering, linear sampling method, microwave imaging, Tmatrix, virtual experiments

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Section: B Imaging Framework Based On T-matrix Methodsmentioning

confidence: 99%

Section: Appendixmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Fast Inverse Scattering Imaging Method by Applying Virtual Experiments to T-Matrix Scheme

et al. 2020

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“…However, Hough transform is computationally expensive. In addition, some image processing methods are used to process radar signals [21,22]. An advanced imaging algorithm was proposed for automated detection of the hyperbola region, which used the Canny edge detector and performed well [21].…”

Section: Introductionmentioning

confidence: 99%

“…In addition, some image processing methods are used to process radar signals [21,22]. An advanced imaging algorithm was proposed for automated detection of the hyperbola region, which used the Canny edge detector and performed well [21]. Extensive research has applied deep learning (DL) techniques to process radar signals [6,[23][24][25].…”

Section: Introductionmentioning

confidence: 99%

Underground Cylindrical Objects Detection and Diameter Identification in GPR B-Scans via the CNN-LSTM Framework

et al. 2020

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Ground penetrating radar (GPR), as a non-invasive instrument, has been widely used in the civil field. The interpretation of GPR data plays a vital role in underground infrastructures to transfer raw data to the interested information, such as diameter. However, the diameter identification of objects in GPR B-scans is a tedious and labor-intensive task, which limits the further application in the field environment. The paper proposes a deep learning-based scheme to solve the issue. First, an adaptive target region detection (ATRD) algorithm is proposed to extract the regions from B-scans that contain hyperbolic signatures. Then, a Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) framework is developed that integrates Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) network to extract hyperbola region features. It transfers the task of diameter identification into a task of hyperbola region classification. Experimental results conducted on both simulated and field datasets demonstrate that the proposed scheme has a promising performance for diameter identification. The CNN-LSTM framework achieves an accuracy of 99.5% on simulated datasets and 92.5% on field datasets.

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3D reconstruction system and multiobject local tracking algorithm designed for billiards

et al. 2023

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The use of virtual reality or augmented reality systems in billiards sports are useful tools for pure entertainment or improving the player’s skills. Depending on the purpose of these systems, tracking algorithms based on computer vision must be used. These algorithms are especially useful in systems aiming to reconstruct the trajectories followed by the balls after a strike. However, depending on the billiard modality, the problem of tracking multiple small identical objects, such as balls, is a complex task. In addition, when an amateur or nontop professional player uses low-frame-rate and low-resolution devices, problems such as blurred balls, blurred contours, or fuzzy edges, among others, arise. These effects have a negative impact on ball-tracking accuracy and reconstruction quality. Thus, this work proposes two contributions. The first contribution is a new tracking algorithm called “multiobject local tracking (MOLT)”. This algorithm can track balls with high precision and accuracy even with motion blur caused by low-resolution and low-frame-rate devices. Moreover, the proposed MOLT algorithm is compared with nine tracking methods and four different metrics, outperforming the rest of the methods in the majority of the cases and providing a robust solution. The second contribution is a whole system to track (using the MOLT algorithm) and reconstruct the movements of the balls on a billiard table in a 3D virtual world using computer vision. The proposed system covers all steps from image capture to 3D reconstruction. The 3D reconstruction results have been qualitatively evaluated by different users through a series of questionnaires, obtaining an overall score of 7.6 (out of 10), which indicates that the system is a promising and useful tool for training. Finally, both the MOLT algorithm and the reconstruction system are tested in three billiard modalities: blackball, carom billiards, and snooker.

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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

Cited by 17 publications

References 48 publications

A Fast Inverse Scattering Imaging Method by Applying Virtual Experiments to T-Matrix Scheme

A Fast Inverse Scattering Imaging Method by Applying Virtual Experiments to T-Matrix Scheme

Underground Cylindrical Objects Detection and Diameter Identification in GPR B-Scans via the CNN-LSTM Framework

3D reconstruction system and multiobject local tracking algorithm designed for billiards

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