A real-time implementation of the Total Focusing Method for rapid and precise diagnostic in non destructive evaluation

Njiki, Mickael; Elouardi, Abdelhafid; Bouaziz, Samir; Casula, O.; Roy, Olivier

doi:10.1109/asap.2013.6567582

Cited by 11 publications

(4 citation statements)

References 8 publications

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“…Fig. 5 shows the evolution of CPP (period per particle) [11] for different implementations. This metric is calculated using the following equation: CPP = f * t M where M is the number of particles, f is the clock frequency represented by Hz, and t is the processing time in seconds.…”

Section: Resultsmentioning

confidence: 99%

OpenCL and OpenGL Implementation of Simultaneous Localization and Mapping Algorithm using High-End GPU

et al. 2022

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Simultaneous Localization And Mapping (SLAM) algorithms are being used in many robotic applications and autonomous navigation systems. The FastSLAM2.0 addresses an issue of the SLAM problem and allows a robot to navigate in an unknown environment. Several works have presented many algorithmic optimizations to reduce the computational complexity of such algorithm. In this paper, a GPGPU (general-purpose computing on graphics processing units) is exploited to achieve a parallel implementation of the FastSLAM2.0. The GPGPU acceleration is done using two different implementations for parallel programming. The first implementation used OpenGL shading language which is based on the characteristics of graphics hardwares. The second implementation used OpenCL which allows hardware acceleration across heterogeneous architectures. We also explored the impact of the two approaches on the the resulting GPGPU implementation. A comparison related to processing-time and localization accuracy is made using a real indoor dataset. Our results show a significant speedup of the GPGPU implementation over a Quad-Core CPU. We show also that, by adopting the same optimization methodology using the two approachs, the OpenCL implementation is faster and suitable for GPGPU accelerated SLAM algorithms.

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Section: Resultsmentioning

confidence: 99%

OpenCL and OpenGL Implementation of Simultaneous Localization and Mapping Algorithm using High-End GPU

et al. 2022

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“…While real time synthetic aperture implementations have been achieved [10], [20], high resolution images created using probes with high element counts must still be produced in post processing. With the full matrix, it is possible to apply numerous processing methods to the same data set.…”

Section: Synthetic Aperture Methodsmentioning

confidence: 99%

“…This is difficult to achieve using synthetic aperture methods, in that the techniques are inherently computationally expensive. As such, high frame rates often cannot be achieved, even when exploiting the parallelisable nature of the calculations [10].…”

Section: Introductionmentioning

confidence: 99%

Investigation of synthetic aperture methods in ultrasound surface imaging using elementary surface types

2016

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Synthetic aperture imaging methods have been employed widely in recent research in non-destructive testing (NDT), but uptake has been more limited in medical ultrasound imaging. Typically offering superior focussing power over more traditional phased array methods, these techniques have been employed in NDT applications to locate and characterise small defects within large samples, but have rarely been used to image surfaces. A desire to ultimately employ ultrasonic surface imaging for bone surface geometry measurement prior to surgical intervention motivates this research, and results are presented for initial laboratory trials of a surface reconstruction technique based on global thresholding of ultrasonic 3D point cloud data. In this study, representative geometry artefacts were imaged in the laboratory using two synthetic aperture techniques; the Total Focusing Method (TFM) and the Synthetic Aperture Focusing Technique (SAFT) employing full and narrow synthetic apertures, respectively. Three high precision metallic samples of known geometries (cuboid, sphere and cylinder) which featured a range of elementary surface primitives were imaged using a 5MHz, 128 element 1D phased array employing both SAFT and TFM approaches. The array was manipulated around the samples using a precision robotic positioning system, allowing for repeatable ultrasound derived 3D surface point clouds to be created. A global thresholding technique was then developed that allowed the extraction of the surface profiles, and these were compared with the known geometry samples to provide a quantitative measure of error of 3D surface reconstruction. The mean errors achieved with optimised SAFT imaging for the cuboidal, spherical and cylindrical samples were 1.3mm, 2.9mm and 2.0mm respectively, while those for TFM imaging were 3.7mm, 3.0mm and 3.1mm, respectively. These results were contrary to expectations given the higher information content associated with the TFM images. However, it was established that the reduced error associated with the SAFT technique was associated with significant reductions in side lobe levels of approximately 24dB in comparison to TFM imaging, although this came at the expense of reduced resolution and coverage.

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“…Lockwood et al proposed sparse synthetic aperture (SSA) system [13]. TFM real-time imaging systems using FPGA parallel computing [14] or GPU solution [15] have been studied.…”

Section: Introductionmentioning

confidence: 99%

Efficient imaging techniques using Sub-aperture matrix capture and two-dimensional sparse array

Yang

Guo

Gao

et al. 2014

2014 IEEE Far East Forum on Nondestructive Evaluation/Testing

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Total focusing method (TFM) is a post-processing algorithm for ultrasonic imaging, usually used for processing linear array data. In this paper, TFM is extended to obtain three-dimensional (3D) image based on two-dimensional array data. However, it takes a long time to get 3D information from large amount of 2D array data by TFM. So Sub-aperture matrix capture (SMC) and sparse array are taken into account to solve this issue. The experimental results prove that TFM precisely reconstruct 3D information of defects through the optimized method. In a small angle imaging range, SMC can reach the same image quality and the same array performance indicator (API) as full matrix capture (FMC). In addition, it won't take more than one quarter of the time token by FMC for ultrasonic imaging. Although the spurious image is enhanced with the reducing sparseness, the processing time is reduced. Considering both image quality and real-time imaging, the imaging efficiency might be improved by 50 times through the combination of the two methods. The paper provides an optional approach to achieve real-time imaging system.

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A real-time implementation of the Total Focusing Method for rapid and precise diagnostic in non destructive evaluation

Abstract: International audienc

Cited by 11 publications

References 8 publications

OpenCL and OpenGL Implementation of Simultaneous Localization and Mapping Algorithm using High-End GPU

OpenCL and OpenGL Implementation of Simultaneous Localization and Mapping Algorithm using High-End GPU

Investigation of synthetic aperture methods in ultrasound surface imaging using elementary surface types

Efficient imaging techniques using Sub-aperture matrix capture and two-dimensional sparse array

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