Application of Heterogeneous Computing Techniques for the Development of an Image-Based Hot Spot Detection System Using MTCA

Esquembri, S.; Nieto, J.; Ruiz, Antonio Carpeño; Ruiz, M.; Astrain, M.; Costa, Víctor; Gracia, Alberto

doi:10.1109/tns.2021.3087124

Cited by 4 publications

(4 citation statements)

References 11 publications

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“…an alternative programming and deployment alternative must be used wh execution time is needed to implement the algorithm in a real-time experim ple, in a nuclear fusion-related diagnostic) [17]. In addition, the use of g cessing units (GPUs) has emerged as a powerful solution for massive da especially in image processing with 1D or 2D detectors and cameras [18,19] There are two different actions intended to reduce algorithm execution the algorithm's steps must be identified, and secondly, the optimization op be evaluated. The methodology used to accelerate the algorithm execution steps:…”

Section: Analysis Of the Different Alternativesmentioning

confidence: 99%

“…Nevertheless, an alternative programming and deployment alternative must be used when a reduced execution time is needed to implement the algorithm in a real-time experiment (for example, in a nuclear fusion-related diagnostic) [17]. In addition, the use of graphical processing units (GPUs) has emerged as a powerful solution for massive data processing, especially in image processing with 1D or 2D detectors and cameras [18,19].…”

Section: Analysis Of the Different Alternativesmentioning

confidence: 99%

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Acceleration of an Algorithm Based on the Maximum Likelihood Bolometric Tomography for the Determination of Uncertainties in the Radiation Emission on JET Using Heterogeneous Platforms

Ruiz

Nieto²,

Costa³

et al. 2022

Applied Sciences

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In recent years, a new tomographic inversion method based on the Maximum Likelihood (ML) approach has been adapted to JET bolometry. Apart from its accuracy and reliability, the key advantage is its ability to provide reliable estimates of the uncertainties in the reconstructions. The original algorithm was implemented and validated using the MATLAB software tool. This work presents the accelerated version of the algorithm implemented using a compatible ITER fast controller platform with the Ubuntu 18.04 or the ITER Codac Core System distributions (6.1.2). The algorithm has been implemented in C++ using the open-source libraries: ArrayFire, ALGLIB, and MATIO. These libraries simplify the management of specific hardware accelerators such as GPUs and increase performance. The speed-up factor obtained is approximately 10 times. The work presents the methodology followed, the results obtained, and the advantages and drawbacks of implementation.

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Section: Analysis Of the Different Alternativesmentioning

confidence: 99%

Section: Analysis Of the Different Alternativesmentioning

confidence: 99%

Acceleration of an Algorithm Based on the Maximum Likelihood Bolometric Tomography for the Determination of Uncertainties in the Radiation Emission on JET Using Heterogeneous Platforms

Ruiz

Nieto²,

Costa³

et al. 2022

Applied Sciences

Self Cite

View full text Add to dashboard Cite

show abstract

“…After the binarization process, the similarity of the gray value between the target pixel and the background pixel represents its connectivity. There are two commonly used types of connected components, namely the 4-connected component and the 8-connected component [ 13 ]. The method of the connected component can quantify and extract the region properties in an image, and then objects in the image can be automatically detected, labeled, and measured.…”

Section: Introductionmentioning

confidence: 99%

Research and Evaluation on an Optical Automatic Detection System for the Defects of the Manufactured Paper Cups

Wang

Lee

Tseng

et al. 2023

Sensors

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In this paper, the paper cups were used as the research objects, and the machine vision detection technology was combined with different image processing techniques to investigate a non-contact optical automatic detection system to identify the defects of the manufactured paper cups. The combined ring light was used as the light source, an infrared (IR) LED matrix panel was used to provide the IR light to constantly highlight the outer edges of the detected objects, and a multi-grid pixel array was used as the image sensor. The image processing techniques, including the Gaussian filter, Sobel operator, Binarization process, and connected component, were used to enhance the inspection and recognition of the defects existing in the produced paper cups. There were three different detection processes for paper cups, which were divided into internal, external, and bottom image acquisition processes. The present study demonstrated that all the detection processes could clearly detect the surface defect features of the manufactured paper cups, such as dirt, burrs, holes, and uneven thickness. Our study also revealed that the average time for the investigated Automatic Optical Detection to detect the defects on the paper cups was only 0.3 s.

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“…After binarizing the image, pixels that have similar gray values are grouped together into a connected component [14]. Two methods of connectivity are commonly used: fourconnected and eight-connected.…”

Section: Introductionmentioning

confidence: 99%

Method and Installation for Efficient Automatic Defect Inspection of Manufactured Paper Bowls

Lee

Chen

et al. 2023

Photonics

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Various techniques were combined to optimize an optical inspection system designed to automatically inspect defects in manufactured paper bowls. A self-assembled system was utilized to capture images of defects on the bowls. The system employed an image sensor with a multi-pixel array that combined a complementary metal-oxide semiconductor and a photo detector. A combined ring light served as the light source, while an infrared (IR) LED matrix panel was used to provide constant IR light to highlight the outer edges of the objects being inspected. The techniques employed in this study to enhance defect inspections on produced paper bowls included Gaussian filtering, Sobel operators, binarization, and connected components. Captured images were processed using these technologies. Once the non-contact inspection system’s machine vision method was completed, defects on the produced paper bowls were inspected using the system developed in this study. Three inspection methods were used in this study: internal inspection, external inspection, and bottom inspection. All three methods were able to inspect surface features of produced paper bowls, including dirt, burrs, holes, and uneven thickness. The results of our study showed that the average time required for machine vision inspections of each paper bowl was significantly less than the time required for manual inspection. Therefore, the investigated machine vision system is an efficient method for inspecting defects in fabricated paper bowls.

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Application of Heterogeneous Computing Techniques for the Development of an Image-Based Hot Spot Detection System Using MTCA

Cited by 4 publications

References 11 publications

Acceleration of an Algorithm Based on the Maximum Likelihood Bolometric Tomography for the Determination of Uncertainties in the Radiation Emission on JET Using Heterogeneous Platforms

Acceleration of an Algorithm Based on the Maximum Likelihood Bolometric Tomography for the Determination of Uncertainties in the Radiation Emission on JET Using Heterogeneous Platforms

Research and Evaluation on an Optical Automatic Detection System for the Defects of the Manufactured Paper Cups

Method and Installation for Efficient Automatic Defect Inspection of Manufactured Paper Bowls

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