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28th International Conference on image and Vision Computing New Zealand (IVCNZ)

作者： Bailey, Donald G. Klaiber, Michael J. Massey Univ Sch Engn & Adv Technol Palmerston North New Zealand Univ Stuttgart Inst Parallel & Distributed Syst Stuttgart Germany

ISBN: (纸本)9781479908837;9781479908820

Calculation of mean, variance and standard deviation are often required for segmentation or feature extraction. In image processing, often an integer approximation is adequate. Conventional methods require division and square root operations, which are expensive to realize in hardware in terms of both the amount of required resources and latency. A new class of iterative algorithms is developed based on integer arithmetic. An implementation of the algorithms as a hardware architecture for a Field-Programmable Gate Array (FPGA) is compared with architectures using the conventional approach, which shows a significantly reduced latency while using less hardware resources.

关键词： Computer hardware hardware resource Field programmable gate arrays hardware architecture Iterative algorithms Feature extraction ARCHITECTURE Integer Latency integer arithmetic segmentation

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A multiway model for predicting earthquake ground motion

A multiway model for predicting earthquake ground motion

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14th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and parallel/distributed Computing, SNPD 2013

作者： Bai, Yang Tezcan, Jale Cheng, Qiang Cheng, Jie Southern Illinois University Carbondale IL 62901 United States University of Hawaii Hilo HI 96720 United States

ISBN: (纸本)9780769550053

This paper develops a novel supervised method for predicting earthquake ground motions in the wavelet domain. The training input is a set of seismological predictors related to seismic source, path and local site conditions, and the training output consists of the weights from a multiway analysis of ground motions. We treat wavelet transforms of acceleration records as images and extract essential patterns from them using tensor decomposition. The decomposition weights of these patterns are then linked to seismological variables using general regression neural network (GRNN). The resulting nonparametric model is then used to predict the wavelet image of an accelerogram for a given set of seismological variables. The predicted image can be transformed back to the time domain using inverse wavelet transform for subsequent processing to match a given design spectrum. Unlike conventional ground motion models, the proposed approach retains the time domain characteristics of ground motions. Pearson's correlation coefficient between the vectorized forms of actual and predicted wavelet images has been used as the similarity metric in assessing the prediction capability of the resulting model. Experimental results demonstrate the ability of the proposed model to predict significant patterns in the seismic energy distribution. © 2013 IEEE.

关键词： Correlation methods

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parallel implementation of a X-ray tomography reconstruction algorithm based on MPI and CUDA 13

Parallel implementation of a X-ray tomography reconstruction...

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20th European MPI Users' Group Meeting, EuroMPI 2013

作者： Blas, Javier Garcia Abella, Monica Liria, Ernesto Isaila, Florin Carretero, Jesus Desco, Manuel Computer Architecture and Communication Area University Carlos III Madrid Spain Bioengineering and Aerospace Engineering IiSGM CIBERSAM Madrid Spain

ISBN: (纸本)9788461651337

Most small-animal X-ray computed tomography (CT) scanners are based on cone-beam geometry with a flat-panel detector orbiting in a circular trajectory. image reconstruction in these systems is usually performed by approximate methods based on the algorithm proposed by Feldkamp, Davis and Kress (FDK). Currently there is a strong need to speedup the reconstruction of X-Ray CT data in order to extend its clinical applications. The evolution of the semiconductor detector panels has resulted in an increase of detector elements density, which produces a higher amount of data to process. This work focuses on future high-resolution studies (density up to 4096 pixeles), in which multiple level of parallelism will be needed in the reconstruction. In addition, this paper addresses the future challenges of processing high-resolution images in many-core and distributed architectures. In our evaluation section we demonstrate that our solution is 17% faster than recent related works. Copyright 2013 ACM.

关键词： parallel architectures

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Visualizing parallelism in CS 2

Visualizing Parallelism in CS 2

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IEEE International Symposium on parallel and distributed processing Workshops and Phd Forum (IPDPSW)

作者： Sean Massung Cinda Heeren Computer Science Dept University of Illinois at Urbana-Champaign

ISBN: (纸本)9781479913725

This paper describes the incorporation of the IEEE-TCPP Curriculum Initiative into CS 2 at the University of Illinois at Urbana-Champaign. With control over only one course that requires a semi-rigid curriculum, we detail a sequence of three lessons that explore the basics of parallelism in a visual manner. We draw a contrast between standard teaching methods for parallelism and assert that our approach is more engaging and more accessible, particularly to spatial learners. We then present examples of our image-centric course material and discuss its deployment. Lastly, we reflect on the effectiveness of this technique over the past two semesters and consider its direction in the future.

关键词： parallel processing Educational institutions Instruction sets image color analysis Visualization Materials Algorithm design and analysis

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distributed and parallel Subarray Beamforming for Near-Field 3D Sonar Imaging

Distributed and Parallel Subarray Beamforming for Near-Field...

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International Conference on Computer Science and Network Technology

作者： Yeqiang Han Jiabao Fu Fan Zhou Xiang Tian Yaowu Chen Inst. of Adv. Digital Technol. & Instrum. Zhejiang Univ. Hangzhou China

ISBN: (纸本)9781479905607

The computational load is prohibitive in 3D sonar systems for real-time image generation. In the literature, an efficient frequency beamforming method based on the distributed and parallel subarray (DPS) has been introduced for planar arrays working in the far field. This paper extends the DPS beamforming algorithm to process the signals acquired from a scene in the near field. The alogrithm divides the full populated transducer array into two stage distributed subarrays. It performs parallel beamforming on the first-stage subarrays and applies the approximation for time delays in the near-field beam patterns of the second-stage subarray. The computational efficiency is significantly improved as compared with the traditional methods, while achieving the similar resolutions. In addition, a multi-FPGA signal processor is proposed for implementing the underwater 3-D imaging.

关键词： array signal processing delay systems field programmable gate arrays sonar imaging DPS beamforming algorithm computational load distributed subarray beamforming frequency beamforming method multiFPGA signal processor near-field 3D sonar imaging near-field beam patterns parallel subarray beamforming real-time image generation time delays Array signal processing Arrays Imaging Signal processing algorithms Sonar Three-dimensional displays distributed and parallel subarray beamforming sonar sensor array system sonar signal processing underwater 3D imaging

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Using clusters in undergraduate research: distributed animation rendering, photo processing, and image transcoding

Using clusters in undergraduate research: Distributed animat...

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IEEE International Conference on Cluster Computing

作者： Peter Bui Travis Boettcher Nicholas Jaeger Jeffrey Westphal Department of Computer Science University of Wisconsin - Eau Claire Eau Claire Wisconsin

With distributed and parallel computing becoming increasingly important in both industrial and scientific endeavors, it is imperative that students are introduced to the challenges and methods of high performance and high throughput computing. Because these topics are often absent in standard undergraduate computer science curriculums, it is necessary to encourage and support independent research and study involving distributed and parallel computing. In this paper, we present three undergraduate research projects that utilize distributed computing clusters: animation rendering, photo processing, and image transcoding. We describe the challenges faced in each project, examine the solutions developed by the students, and then evaluate the performance and behavior of each system. At the end, we reflect on our experience using distributed clusters in undergraduate research and offer six general guidelines for mentoring and pursing distributed computing research projects with undergraduates. Overall, these projects effectively promote skills in high performance and high throughput computing while enhancing the undergraduate educational experience.

关键词： Computers Animation Browsers Transcoding Reliability

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A Laplace transform method for the image in-painting

A Laplace transform method for the image in-painting

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The 12th International Symposium on distributed Computing and Applications to Business,Engineering and Science(DCABES 2013)(第十二届分布式计算及其应用国际学术研讨会)

作者： N.Kokulan C.-H.Lai School of Computing and Mathematical Sciences University of Greenwich London UK

There are many image processing techniques based on partial differential equations that perform well,but they consume much computational ***'s vital that rapid and efficient ways of solving these equations are *** of the Laplace transforms permits solution to the time dependent problems in a parallel *** solution procedure requires numerical computation of an inverse Laplace transform of which the Stehfest method was examined in the *** investigated the performance and efficiency of using the Laplace transform technique for the solution of a mathematical model related to image in-painting and compared the results with temporal integration.

关键词： CDD in-painting temporal parallel methods time dependent problems

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Multi-label Classification with Clustering for image and Text Categorization

Multi-label Classification with Clustering for Image and Tex...

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International Congress on image and Signal processing

作者： Gulisong Nasierding Atul Sajjanhar School of Computer Science and Technology Xinjiang Normal University Parallel and Distributed Computing Lab School of Information Technology Deakin University

ISBN: (纸本)9781479927654

This paper explores effective multi-label classification methods for multi-semantic image and text categorization. We perform an experimental study of clustering based multi-label classification (CBMLC) for the target problem. Experimental evaluation is conducted for identifying the impact of different clustering algorithms and base classifiers on the predictive performance and efficiency of CBMLC. In the experimental setting, three widely used clustering algorithms and six popular multi-label classification algorithms are used and evaluated on multi-label image and text datasets. A multi-label classification evaluation metrics, micro F1-measure, is used for presenting predictive performances of the classifications. Experimental evaluation results reveal that clustering based multi-label learning algorithms are more effective compared to their non-clustering counterparts.

关键词： Multi-label classification Clustering image and text categorization

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Efficient hardware calculation of running statistics

Efficient hardware calculation of running statistics

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International Conference on image and Vision Computing New Zealand, IVCNZ

作者： Donald G. Bailey Michael J. Klaiber School of Engineering and Advanced Technology Massey University Palmerston North Institute for Parallel and Distributed Systems University of Stuttgart

关键词： Hardware Computer architecture Standards Approximation methods Nickel Accuracy Feature extraction

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A parallel solution for high resolution histological image analysis

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COMPUTER methods AND PROGRAMS IN BIOMEDICINE 2012年第1期108卷 388-401页

作者： Bueno, G. Gonzalez, R. Deniz, O. Garcia-Rojo, M. Gonzalez-Garcia, J. Fernandez-Carrobles, M. M. Vallez, N. Salido, J. Univ Castilla La Mancha VISILAB ETS Ingenieros Ind E-13071 Ciudad Real Spain Hosp Gen Univ Ciudad Real Dpt Anat Patol Ciudad Real Spain

This paper describes a general methodology for developing parallel image processing algorithms based on message passing for high resolution images (on the order of several Gigabytes). These algorithms have been applied to histological images and must be executed on massively parallel processing architectures. Advances in new technologies for complete slide digitalization in pathology have been combined with developments in biomedical informatics. However, the efficient use of these digital slide systems is still a challenge. The image processing that these slides are subject to is still limited both in terms of data processed and processing methods. The work presented here focuses on the need to design and develop parallel image processing tools capable of obtaining and analyzing the entire gamut of information included in digital slides. Tools have been developed to assist pathologists in image analysis and diagnosis, and they cover low and high-level image processing methods applied to histological images. Code portability, reusability and scalability have been tested by using the following parallel computing architectures: distributed memory with massive parallel processors and two networks, INFINIBAND and Myrinet, composed of 17 and 1024 nodes respectively. The parallel framework proposed is flexible, high performance solution and it shows that the efficient processing of digital microscopic images is possible and may offer important benefits to pathology laboratories. (c) 2012 Elsevier Ireland Ltd. All rights reserved.

关键词： Low and high-level parallel image processing High resolution histological image processing MPI Microscopy Whole slide imaging

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