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IASTED International Conference on parallel and distributed Computing and Systems, PDCS 2011

作者： Zhao, Jingxiu Xiang, Yonghong Dawson, Laurence Wart, Iain St School of Computer Science Qufu Normal University Rizhao 276826 China School of Engineering and Computing Sciences Durham University Durham DH1 3LE United Kingdom

ISBN: (纸本)9780889869073

In this paper, we present a new method for quantifying color information so as to detect edges in color images. Our method uses the volume of a pixel in the HSI color space, allied with noise reduction, thresholding and edge thinning. We implement our algorithm using NVIDIA Compute Unified Device Architecture (CUDA) for direct execution on Graphics processing Units (GPUs). Our experimental results show that: compared to traditional edge detection methods, our method can improve the accuracy of edge detection and withstand greater levels of noise in images;and our GPU implementation achieves speedups over related CUDA implementations.

关键词： Graphics processing unit

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Performance Analysis of Mammographic image Enhancement Techniques for Early Detection of Breast Cancer

Performance Analysis of Mammographic Image Enhancement Techn...

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1st International Conference on Computer Science, Engineering and Information Technology (CCSEIT 2011)

作者： Singh, Shailaja Yadav, Anamika Singh, Bikesh Kumar MPCCET Dept Comp Sci & Engn Bhilai India NIT Dept Elect Engn Raipur Madhya Pradesh India

ISBN: (纸本)9783642240362;9783642240379

Mammogram breast cancer images have the ability to assist physician in detection of disease caused by cells normal growth. Developing algorithms and software to analyse these images may also assist physicians in their daily work. Micro calcifications are tiny calcium deposits in breast tissues. They appear as small bright spots on mammograms. Since micro calcifications are small and subtle abnormalities, they may he overlooked by an examining radiologist. image Enhancement and Filtering is always the root process in many medical image processing applications. It is aimed at reducing noise in images. In this paper we have made comparison between several novel and hybrid enhancement techniques. The comparison is based on the basis of performance evaluation parameters (statistical parameter) such as PSNR, and CNR. These can be used for identifying breast nodule malignancy to provide better chance of a proper treatment. These methods are tested on digital mammograms present in mini-MIAS database.

关键词： Mammograms image Enhancement Spatial Filtering Contrast to noise ratio (CNR) Signal to noise ratio (PSNR)

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基于FPGA超声信号数字动态滤波器的实现

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现代生物医学进展 2012年第2期12卷 344-347页

作者：朱利华武剑辉栾强厚电子科技大学生命科学与技术学院四川成都610054 东莞电子科技大学电子信息工程研究院广东东莞523808

目的:本文研究了基于现场可编程门阵列(Field Programmable Gate Array,FPGA)超声成像系统中数字动态滤波器的实现方法和过程。方法:动态滤波器中FIR滤波器采用分布式算法(distributed Arithmetic,DA)实现结构,并在应用中对DA算法进行... 详细信息

目的:本文研究了基于现场可编程门阵列(Field Programmable Gate Array,FPGA)超声成像系统中数字动态滤波器的实现方法和过程。方法:动态滤波器中FIR滤波器采用分布式算法(distributed Arithmetic,DA)实现结构,并在应用中对DA算法进行了改进,包括数据并行处理结构的设计、对查找表(Look Up Table,LUT)输入字长N大小的控制和具有对称系数的FIR滤波器的采用。改进后的DA实现在FPGA资源占用和处理速度之间达到了平衡。同时,结合多级流水线结构,动态滤波器实现了数字超声信号并行处理。结果:采用常值滤波器(远场匹配参数)进行滤波后,超声回波图像远场分辨率达到了要求,但越靠近近场效果越差。相比之下,本文设计的基于FPGA超声信号动态数字滤波器达到了很好的滤波效果,使回声图像近场和远场都有最佳分辨率。结论:利用FPGA实现超声系统中动态滤波器是完全可行的,并且有助于提高系统的稳定性和可靠性,并大大减低系统成本。

关键词：超声信号动态滤波分布式算法 FIR滤波器 FPGA

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Biomedical image processing with GPGPU using CUDA

Biomedical image processing with GPGPU using CUDA

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作者： Firstauthor, A.R. Secondauthor, I.B. Thirdauthor, G.V. Fourthauthor, P.B. Fifthauthor, M.K. Buda University John von Neumann Faculty of Informatics Budapest Hungary Semmelweiss University 2nd Department of Internal Medicine Budapest Hungary MTA SZTAKI Laboratory of Parallel and Distributed Computing Budapest Hungary

ISBN: (纸本)9789532330670

The main aim of this work is to show, how the GPGPUs can be used to speed up certain image processing methods. The algorithm explained in this paper is used to detect nuclei on (HE hematoxilin eosin) stained colon tissue sample images, and includes a Gauss blurring, an RGB-HSV color space conversion, a fixed binarization, an ultimate erode procedure and a local maximum search. Since the images retrieved from the digital slides require significant storage space (up to few hundred megapixels), the usage of GPGPUs to speed up image processing operations is necessary in the interest of achieving reasonable processing time. The CUDA software development kit was used to develop algorithms to GPUs made by NVIDIA. This work focuses on how to achieve coalesced global memory access when working with three-channel RGB images, and how to use the on-die shared memory efficiently. The exact test algorithm also included a linear connected component labeling, which was running on the CPU, and with iterative optimization of the GPU code, we managed to achieve significant speed up in well defined test environment. © 2011 MIPRO.

关键词： Iterative methods

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Research on Acquisition methods of High-Precision DEM for distributed Hydrological Model

Research on Acquisition Methods of High-Precision DEM for Di...

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4th IFIP TC 12 Conference on Computer and Computing Technologies in Agriculture

作者： Deng, Li Liang, Yong Zhang, Chengming Shandong Agr Univ Sch Informat Sci & Engn Tai An 271018 Shandong Peoples R China

ISBN: (纸本)9783642183539

Compared with the traditional lumped hydrological models, distributed hydrological model, considering the effects of the uneven spatial distribution of watershed land surface on the hydrological cycle, has the characteristic of physical mechanism. Seeing from overall structure, there are two types of distributed hydrological model, which are runoff and convergence. The establishment of convergence network is on the basis of calculating reservoir routing convergence, at present, converged networks are constructed on the grounds of DEM, the resolution of DEM directly affects the result of convergence network construction, for now, due to confidentiality rules, it is very difficult to obtain high-resolution DEM. With the development of GIS and RS, it is more convenient to acquire data from distributed hydrological model, which has been developing rapidly. SRTM is completed by the National Aeronautics and Space Administration (NASA), National image Mapping Agency (NIMA) and the German and Italian space agencies. The current publicly available data resolution is 3 arc seconds (1 / 1200 of longitude and latitude), and its length is equivalent to 90 meters. The publication of this data set is an important breakthrough in geographical science and application, which has important application value. However, because of the limitations on using radar technology to obtain surface elevation data, there are many problems in the original SRTM DEM data, such as missing more regional data, existing many abnormal points, and so on. This article, which takes Xue Ye reservoir area as example, studies the methods of processing SRTM data and obtained high-resolution DEM data of the region.

关键词： NASA

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parallel Implementation of Edge-Directed image Interpolation on a Graphics processing Unit

Parallel Implementation of Edge-Directed Image Interpolation...

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International Conference on parallel and distributed Systems (ICPADS)

作者： Jiaji Wu Tao Li Bormin Huang School of Electronic Engineering Xidian University Xi'an China Space Science and Engineering Center University of Wisconsin-Madison Madison USA

The edge-directed interpolation scheme is a non-iterative, orientation-adaptive method to enhance image resolution with better visual effect than conventional interpolation methods. It interpolates the missing pixels based on the covariance of a high-resolution image estimated from the covariance of the low-resolution image. In spite of the impressive performance, the computational complexity of covariance-based adaptation is significantly higher than that of the conventional linear interpolation algorithms. In this paper, we propose a GPU-based massively parallel version of the edge-directed interpolation scheme. A speedup of 61.7x can be achieved with respect to its single-threaded CPU counterpart in the host computer.

关键词： Interpolation Graphics processing unit Instruction sets image edge detection Streaming media Kernel Registers

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PATUS: A Code Generation and Autotuning Framework for parallel Iterative Stencil Computations on Modern Microarchitectures

PATUS: A Code Generation and Autotuning Framework for Parall...

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International Symposium on parallel and distributed processing (IPDPS)

作者： Matthias Christen Olaf Schenk Helmar Burkhart Department of Mathematics and Computer Science University of Basel Switzerland

Stencil calculations comprise an important class of kernels in many scientific computing applications ranging from simple PDE solvers to constituent kernels in multigrid methods as well as image processing applications. In such types of solvers, stencil kernels are often the dominant part of the computation, and an efficient parallel implementation of the kernel is therefore crucial in order to reduce the time to solution. However, in the current complex hardware micro architectures, meticulous architecture-specific tuning is required to elicit the machine's full compute power. We present a code generation and auto-tuning framework \textsc{Patus} for stencil computations targeted at multi- and many core processors, such as multicore CPUs and graphics processing units, which makes it possible to generate compute kernels from a specification of the stencil operation and a parallelization and optimization strategy, and leverages the auto tuning methodology to optimize strategy-dependent parameters for the given hardware architecture.

关键词： Hardware Kernel Instruction sets parallel processing Arrays Three dimensional displays

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parallel Automatic Registration of Large Scale Microscopic images on Multiprocessor CPUs and GPUs

Parallel Automatic Registration of Large Scale Microscopic I...

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

作者： Lee Cooper Kun Huang Manuel Ujaldon Center of Comprehensive Informatics Emory University Atlanta GA USA Biomedical Informatics Department Ohio State Uinversity Columbus OH USA Computer Architecture Department University of Malaga Malaga Spain

During the present decade, emerging architectures like multicore CPUs and graphics processing units (GPUs) have steadily gained popularity for their ability to deploy high computational power at a low cost. In this paper, we combine parallelization techniques on a cooperative cluster of multicore CPUs and multisocket GPUs to apply their joint computational power to an automatic image registration algorithm intended for the analysis of high-resolution microscope images. Registration methods pose a computational challenge within the biomedical field due to the large size of microscope image data sets, which typically extend to the Terabyte scale. We analyze this application to identify those parts which are more favorable to the CPU and GPU execution models and decompose the process accordingly. Performance results are presented for two sets of images: mouse placenta (16K × 16K pixels) and mouse mammary tumor (23K × 62K pixels). Execution times are shown on different multi-node, multi-socket and multi-core configurations to provide performance insights about the most effective approach.

关键词： Graphics processing unit Microscopy Multicore processing Sockets Random access memory parallel processing Hardware

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Ball Detection with the Aim of Corner Event Detection in Soccer Video

Ball Detection with the Aim of Corner Event Detection in Soc...

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IEEE International Symposium on parallel and distributed processing with Applications Workshops (ISPAW)

作者： J. Hossein-Khani H. Soltanian-Zadeh M. Kamarei O. Staadt CIPCE Department of Electrical and Computer Engineering University of Tehran Tehran Iran Faculty of Computer Science University of Rostock Rostock Germany

In the present work, automatic corner detection in soccer games based on image features (e.g., object-based features) has been studied. For this purpose, a framework has been proposed that consists of five steps. This paper mainly focuses on the first three steps and specially ball detection step. Ball position on the field plays an important role in determining which event has occurred in the game. Therefore, it is necessary to detect exact position of the ball in the playfield and then track it. Ball trajectory that can be obtained via tracking is useful for identifying and detecting main events of soccer games. In these three steps, the most important processing that has been applied to the images is based on image segmentation to detect playfield, field lines, and ball. Cleaning morphological method is applied to detect the ball. This method is real-time and automatic, it yields superior results in comparison with other common methods such as Template Matching and Circular Hough Transform (CHT). By applying the proposed method, only one candidate for the ball position is obtained and non-ball candidates are removed, hence, it is more reliable than other methods. The results of the proposed method are compared with those of CHT. They illustrate that the proposed method is fast, effective, and reliable.

关键词： image color analysis Streaming media Feature extraction Shape Games Tracking Pixel

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Tracking Structure of Streaming Social Networks

Tracking Structure of Streaming Social Networks

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

作者： David Ediger Jason Riedy David A. Bader Henning Meyerhenke College of Computing Georgia Institute of Technology Atlanta GA USA

Current online social networks are massive and still growing. For example, Face book has over 500 million active users sharing over 30 billion items per month. The scale within these data streams has outstripped traditional graph analysis methods. Real-time monitoring for anomalies may require dynamic analysis rather than repeated static analysis. The massive state behind multiple persistent queries requires shared data structures and flexible representations. We present a framework based on the STINGER data structure that can monitor a global property, connected components, on a graph of 16 million vertices at rates of up to 240,000 updates per second on 32 processors of a Cray XMT. For very large scale-free graphs, our implementation uses novel batching techniques that exploit the scale-free nature of the data and run over three times faster than prior methods. Our framework handles, for the first time, real-world data rates, opening the door to higher-level analytics such as community and anomaly detection.

关键词： Arrays Program processors Facebook image color analysis Hardware

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