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Conference on image processing - Machine Vision applications Vii

作者： Bonifazi, Giuseppe Serranti, Silvia Univ Roma La Sapienza Dept Chem Engn Mat & Environm I-00184 Rome Italy

ISBN: (纸本)9780819499417

In secondary raw materials and recycling sectors, the products quality represents, more and more, the key issue to pursuit in order to be competitive in a more and more demanding market, where quality standards and products certification play a preheminent role. These goals assume particular importance when recycling actions are applied. Recovered products, resulting from waste materials, and/or dismissed products processing, are, in fact, always seen with a certain suspect. An adequate response of the industry to the market can only be given through the utilization of equipment and procedures ensuring pure, high-quality production, and efficient work and cost. All these goals can be reached adopting not only more efficient equipment and layouts, but also introducing new processing logics able to realize a full control of the handled material flow streams fulfilling, at the same time, i) an easy management of the procedures, ii) an efficient use of the energy, iii) the definition and set up of reliable and robust procedures, iv) the possibility to implement network connectivity capabilities finalized to a remote monitoring and control of the processes and v) a full data storage, analysis and retrieving. Furthermore the ongoing legislation and regulation require the implementation of recycling infrastructure characterised by high resources efficiency and low environmental impacts, both aspects being strongly linked to the waste materials and/or dismissed products original characteristics. For these reasons an optimal recycling infrastructure design primarily requires a full knowledge of the characteristics of the input waste. What previously outlined requires the introduction of a new important concept to apply in solid waste recycling, the recycling-oriented characterization, that is the set of actions addressed to strategically determine selected attributes, in order to get goal-oriented data on waste for the development, implementation or improvement of recycling

关键词： Industrial processing solid waste recycling hyperspectral imaging NIR spectroscopy quality control and certification

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Enabling FPGA support in MATLAB based Heterogeneous systems

Enabling FPGA support in MATLAB based Heterogeneous Systems

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2014 International Conference on Reconfigurable Computing and FAGAs

作者： Skalicky, Sam Kwolek, Tyler Lopez, Sonia Lukowiak, Marcin Rochester Inst Technol Rochester NY 14623 USA

ISBN: (纸本)9781479959440

FPGAs have been shown to provide orders of magnitude improvement over CPUs and GPUs in terms of absolute performance and energy efficiency for various kernels such as Cholesky decomposition, matrix inversion, and FFT among others. Despite this, the overall performance of many applications suffer when implemented entirely in FPGAs. Combining FPGAs with CPUs and GPUs provides the range of capabilities needed to support diverse computational requirements of applications. Integrating FPGAs into these systems challenges application developers with constructing hardware kernel implementations and interfacing from the low level hardware logic in the FPGA to the high speed networks that connect processors in the system. In this work we extend the compute capabilities of MATLAB by incorporating support for FPGAs and automating the parallel code generation. We characterize the system and evaluate the performance gains that can be achieved by adding the FPGA for two compute intensive applications. We present performance results for medical imaging and fluid dynamics applications implemented in a CPU+GPU+FPGA system and achieved up to 40x improvement compared to the standard MATLAB CPU+GPU environment.

关键词： computational fluid dynamics fast Fourier transforms field programmable gate arrays graphics processing units mathematics computing matrix inversion medical image processing multiprocessing systems parallel processing parallelising compilers CPU Cholesky decomposition FFT FPGA support GPU MATLAB based heterogeneous systems absolute performance application development computational requirements compute intensive application energy efficiency fluid dynamics application hardware kernel implementation high speed network low level hardware logic medical imaging parallel code generation performance gains processor connection Field programmable gate arrays Graphics processing units Hardware Instruction sets Kernel MATLAB

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Irregular Large-Scale Computed Tomography on Multiple Graphics Processors Improves Energy-Efficiency Metrics for Industrial applications 15

Irregular Large-Scale Computed Tomography on Multiple Graphi...

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Conference on Radiation Detectors - systems and applications xV

作者： Jimenez, Edward S. Goodman, Eric L. Park, Ryeojin Orr, Laurel J. Thompson, Kyle R. Sandia Natl Labs Software Syst R&D POB 5800Mail Stop 0933 Albuquerque NM 87123 USA Sandia Natl Labs Struct Dynam & X ray NDE Albuquerque NM USA ASML US Wilton CT 06897 USA

ISBN: (纸本)9781628412420

This paper will investigate energy-efficiency for various real-world industrial computed-tomography reconstruction algorithms, both CPU-and GPU-based implementations. This work shows that the energy required for a given reconstruction is based on performance and problem size. There are many ways to describe performance and energy efficiency, thus this work will investigate multiple metrics including performance-per-watt, energy-delay product, and energy consumption. This work found that irregular GPU-based approaches(1) realized tremendous savings in energy consumption when compared to CPU implementations while also significantly improving the performance-per-watt and energy-delay product metrics. Additional energy savings and other metric improvement was realized on the GPU-based reconstructions by improving storage I/O by implementing a parallel MIMD-like modularization of the compute and I/O tasks.

关键词： Reconstruction algorithms Energy efficiency x-rays image processing Computed tomography Visualization x-ray imaging Computing systems CT reconstruction x-ray computed tomography

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parallel Implementation of the Modified Vertex Component Analysis Algorithm for Hyperspectral Unmixing Using OpenCL

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IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 2014年第8期7卷 3650-3659页

作者： Callico, Gustavo M. Lopez, Sebastian Aguilar, Beatriz Lopez, Jose F. Sarmiento, Roberto Univ Las Palmas Gran Canaria ULPGC Inst Appl Microelect IUMA E-35017 Las Palmas Gran Canaria Spain

Hyperspectral imaging represents the state-of-the-art technique in those applications related to environmental monitoring, military surveillance, or rare mineral detection. However, one of the requirements of paramount importance when dealing with such scenarios is the ability to achieve real-time constraints taking into account the huge amount of data involved in processing this type of images. In this paper, the authors present for the first time a combination of the newly introduced modified vertex component analysis (MVCA) algorithm for the process of endmembers extraction together with the ability of GPUs to exploit its parallelism, giving, as a result, important speedup factors with respect to its sequential counterpart, while maintaining the same levels of endmember extraction accuracy than the vertex component analysis (VCA) algorithm. Furthermore, OpenCL ensures the use of generic computing platforms without being restricted to a particular vendor. The proposed approach has been assessed on a set of synthetic images as well as on the well-known Cuprite real image, showing that the most time-consuming operations are located on the matrix projection and the maximum search processes. Comparison of the proposed technique with a single-threaded C-based implementation of the MVCA algorithm shows a speedup factor of 8.87 for a 500x500 pixel artificial image with 20 endmembers and 7.14 for the well-known Cuprite hyperspectral data set, including in both cases I/O transfers. Moreover, when the proposed implementation is compared with respect to a C-based sequential implementation of the VCA algorithm, a speedup of 115 has been achieved. In all the cases, the results obtained by the MVCA are the same as the ones obtained with the VCA;thus, the accuracy of the proposed algorithm is not compromised.

关键词： Graphics processing unit (GPU) hyperspectral imaging modified vertex component analysis (MVCA) OpenCL spectral unmixing

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FPGA-based Architecture for Hyperspectral Endmember Extraction 4

FPGA-based Architecture for Hyperspectral Endmember Extracti...

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Conference on High-Performance Computing in Remote Sensing IV

作者： Rosario, Joao Nascimento, Jose M. P. Vestias, Mario Inst Super Engn Lisboa Lisbon Portugal

ISBN: (纸本)9781628413106

Hyperspectral instruments have been incorporated in satellite missions, providing data of high spectral resolution of the Earth. This data can be used in remote sensing applications, such as, target detection, hazard prevention, and monitoring oil spills, among others. In most of these applications, one of the requirements of paramount importance is the ability to give real-time or near real-time response. Recently, onboard processing systems have emerged, in order to overcome the huge amount of data to transfer from the satellite to the ground station, and thus, avoiding delays between hyperspectral image acquisition and its interpretation. For this purpose, compact reconfigurable hardware modules, such as field programmable gate arrays (FPGAs) are widely used. This paper proposes a parallel FPGA-based architecture for endmember's signature extraction. This method based on the Vertex Component Analysis (VCA) has several advantages, namely it is unsupervised, fully automatic, and it works without dimensionality reduction (DR) pre-processing step. The architecture has been designed for a low cost xilinx Zynq board with a Zynq-7020 SoC FPGA based on the Artix-7 FPGA programmable logic and tested using real hyperspectral data sets collected by the NASA's Airborne Visible Infra-Red imaging Spectrometer (AVIRIS) over the Cuprite mining district in Nevada. Experimental results indicate that the proposed implementation can achieve real-time processing, while maintaining the methods accuracy, which indicate the potential of the proposed platform to implement high-performance, low cost embedded systems, opening new perspectives for onboard hyperspectral image processing.

关键词： Hyperspectral Endmember Extraction Vertex Component Analysis (VCA) Field-Programmable Gate Arrays (FPGA) Onboard processing

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Graphics processing Units Accelerated MIMO Tomographic image Reconstruction Using Target Sparseness 3

Graphics Processing Units Accelerated MIMO Tomographic Image...

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Conference on Compressive Sensing iiI

作者： Bello-Maldonado, Pedro D. Rivera-Longoria, Agustin Idleman, Mark Jin, Yuanwei Lu, Enyue Florida Int Univ Dept Elect & Comp Engn Miami FL 33199 USA Texas State Univ Dept Comp Sci San Marcos TX 78666 USA Amherst Coll Dept Comp Sci Amherst MA 01002 USA Univ Maryland Eastern Shore Dept Engn & Aviat Sci Princess Anne MD 21853 USA Salisbury Univ Dept Math & Comp Sci Salisbury MD USA

ISBN: (纸本)9781628410464

GPU computing of medical imaging applications adds an extra layer of acceleration after mathematical algorithms are used to reduce computation times. Our work improves the performance of the multiple-input multiple-output ultrasonic tomography algorithm, by using target sparseness and GPUs with CUDA. The main goal was to determine how GPUs can be best used to accelerate sparsity-aware algorithms for ultrasonic tomography applications. We present smart kernels to compute portions of the algorithm that exploit GPU resources such as shared memory and computing units that can be applied to other applications. Using our accelerated algorithm, we analyze different sparsity constraints setups and evaluate how GPU ultrasonic tomography with target sparseness behaves against the same algorithm that does not incorporate prior knowledge of target sparseness.

关键词： Ultrasonic tomography GPU CUDA sparseness imaging algorithms parallel programming

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5th International Conference in image processing and Communications, IP&C 2013

5th International Conference in Image Processing and Communi...

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5th International Conference in image processing and Communications, IP&C 2013

ISBN: (纸本)9783319016214

The proceedings contain 52 papers. The special focus in this conference is on image processing and Communications. The topics include: Adaptive windowed threshold for box counting algorithm in cytoscreening applications;corneal endothelial grid structure factor based on coefficient of variation of the cell sides lengths;a distributed approach for development of deformable model-based segmentation methods;enhancement of low-dose CT brain scans using graph-based anisotropic interpolation;using of EM algorithm to image reconstruction problem with tomography noises;the perception of humanoid robot by human;a fast histogram estimation based on the Monte Carlo method for image binarization;adaptation of the combined image similarity index for video sequences;time-frequency analysis of image based on stockwell transform;2DKLT-based color image watermarking;knowledge transformations applied in image classification task;problems of infrared and visible-light images automatic registration;semantics driven table understanding in born-digital documents;contextual possibilistic knowledge diffusion for images classification;image feature extraction using compressive sensing;a modification of the parallel spline interpolation algorithms;local Eigen background substraction;polarization imaging in 3D shape reconstrucion;layer image components geometry optimization;extraction of data from limnigraf chart images;a simplified visual cortex model for efficient image codding and object recognition;fuzzy rule-based systems for optimizing power consumption in data centers;an algorithm for finding shortest path tree using ant colony optimization metaheuristic and a sensor network gateway for IP network and SQL database.

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Dependency-Based Automatic parallelization of Java applications

Dependency-Based Automatic Parallelization of Java Applicati...

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20th Euro-Par International Workshops

作者： Rafael, Joao Correia, Ivo Fonseca, Alcides Cabral, Bruno Univ Coimbra P-3000 Coimbra Portugal

ISBN: (纸本)9783319143132;9783319143125

There are billions of lines of sequential code inside nowadays software which do not benefit from the parallelism available in modern multicore architectures. Transforming legacy sequential code into a parallel version of the same programs is a complex and cumbersome task. Trying to perform such transformation automatically and without the intervention of a developer has been a striking research objective for a long time. This work proposes an elegant way of achieving such a goal. By targeting a task-based runtime which manages execution using a task dependency graph, we developed a translator for sequential JAVA code which generates a highly parallel version of the same program. The translation process interprets the AST nodes for signatures such as read-write access, execution-flow modifications, among others and generates a set of dependencies between executable tasks. This process has been applied to well known problems, such as the recursive Fibonacci and FFT algorithms, resulting in versions capable of maximizing resource usage. For the case of two CPU bounded applications we were able to obtain 10.97x and 9.0x speedup on a 12 core machine.

关键词： Automatic programming automatic parallelization task-based runtime symbolic analysis recursive procedures

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Novel Iterative Reconstruction method for optimal dose usage in redundant CT-acquisitions

Novel Iterative Reconstruction method for optimal dose usage...

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Medical imaging - Physics of Medical imaging

作者： Bruder, H. Raupach, R. Allmendinger, T. Kappler, S. Sunnegardh, J. Stierstorfer, K. Flohr, T. Siemens Sect Healthcare Computed Tomog Forchheim Germany

ISBN: (纸本)9780819498267

In CT imaging, a variety of applications exist where reconstructions are SNR and/or resolution limited. However, if the measured data provide redundant information, composite image data with high SNR can be computed. Generally, these composite image volumes will compromise spectral information and/or spatial resolution and/or temporal resolution. This brings us to the idea of transferring the high SNR of the composite image data to low SNR (but high resolution) 'source' image data. It was shown that the SNR of CT image data can be improved using iterative reconstruction [1]. We present a novel iterative reconstruction method enabling optimal dose usage of redundant CT measurements of the same body region. The generalized update equation is formulated in image space without further referring to raw data after initial reconstruction of source and composite image data. The update equation consists of a linear combination of the previous update, a correction term constrained by the source data, and a regularization prior initialized by the composite data. The efficiency of the method is demonstrated for different applications: (i) Spectral imaging we have analysed material decomposition data from dual energy data of our photon counting prototype scanner: the material images can be significantly improved transferring the good noise statistics of the 20 keV threshold image data to each of the material images. (ii) Multi-phase liver imaging: Reconstructions of multi-phase liver data can be optimized by utilizing the noise statistics of combined data from all measured phases (iii) Helical reconstruction with optimized temporal resolution: splitting up reconstruction of redundant helical acquisition data into a short scan reconstruction with Tam window optimizes the temporal resolution The reconstruction of full helical data is then used to optimize the SNR. (iv) Cardiac imaging: the optimal phase image (best phase') can be improved by transferring all applied over radiation

关键词： Iterative Reconstruction Gaussian noise model Low-Contrast Detectability spatial resolution non-linear image processing Dual Energy imaging photon counting detector Multi-phase liver imaging Cardiac imaging Dual Source Computed Tomography

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FPGA implementation of a modified pulse mode FCM image segmentation algorithms

FPGA implementation of a modified pulse mode FCM image segme...

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International image processing, applications and systems Conference (IPAS)

作者： Marwa Karray Mohamed Krid Amir Gargouri Dorra Sellami Masmoudi Computers Imaging Electronics and Systems Group (CIELS) from Sfax Engineering School Sfax Tunisia

This paper present a novel architecture for image segmentation. The design is based on the fuzzy c-means algorithm based gaussian function in pulse mode for reducing the large storage requirement. The proposed algorithm is tested in mammogram image segmentation approximately with 0.92 of segmentation index. The pulse mode stochastic computing technique is implemented with a simple bloc avoiding the use of conventional multipliers for sake of compactness. The whole modified FCM is implemented on a Virtex ii PRO FPGA platform and synthesis results are presented.

关键词： image segmentation Indexes Algorithm design and analysis Clustering algorithms Computer architecture Registers Field programmable gate arrays

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