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Conference on Sensing for Agriculture and Food Quality and Safety iv

作者： Lee, Hoyoung Park, Soo Hyun Kim, Moon S. Noh, Sang Ha Seoul Natl Univ Dept Biosyst & Biomat Sci & Engn Seoul 151921 South Korea Seoul Natl Univ Res Inst Agr & Life Sci Seoul 151921 South Korea USDA Anim Nat Resources Inst Environm Microbiol & Food Safety Lab Beltsville MD 20705 USA

ISBN: (纸本)9780819490476

There are a lot of methods to acquire multispectral images. Dynamic band selective and area-scan multispectral camera has not developed yet. This research focused on development of a filter exchangeable 3CCD camera which is modified from the conventional 3CCD camera. The camera consists of F-mounted lens, image splitter without dichroic coating, three bandpass filters, three image sensors, filer exchangeable frame and electric circuit for parallel image signal processing. In addition firmware and application software have developed. Remarkable improvements compared to a conventional 3CCD camera are its redesigned image splitter and filter exchangeable frame. Computer simulation is required to visualize a pathway of ray inside of prism when redesigning image splitter. Then the dimensions of splitter are determined by computer simulation which has options of BK7 glass and non-dichroic coating. These properties have been considered to obtain full wavelength rays on all film planes. The image splitter is verified by two line lasers with narrow waveband. The filter exchangeable frame is designed to make swap bandpass filters without displacement change of image sensors on film plane. The developed 3CCD camera is evaluated to application of detection to scab and bruise on Fuji apple. As a result, filter exchangeable 3CCD camera could give meaningful functionality for various multispectral applications which need to exchange bandpass filter.

关键词： 3 CCD image splitter multispectral imaging surface defect Fuji apple

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A Study on Reliability and Performance Improvement of distributed System for Large-Scale Data processing

A Study on Reliability and Performance Improvement of Distri...

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作者： Yasuhiro KIRIHATA Osaka University

This dissertation is a study on reliability and performance improvement of distributed system for large-scale data processing researched through 1999 to 2012 by the author who is enrolled at Hitachi Solutions, Ltd. and Graduate School of Information Science and Technology, Osaka University. Recently, as the growth rate of data is getting larger, technologies of storing and processing data at low cost are essential in enterprises and organizations. Because the prices of high-performance commodity servers are going down, it is more popular to construct a cluster or a distributed system of those machines for parallel and distributed data processing of the large-scale data set. In those distributed systems, security, performance, scalability, and availability are principal measures of the system. In terms of the security perspective, the thin client system is one of the effective security methods for the distributed systems dealing with a great number of files in the central file servers. However, it does not diffuse because of its expensive introduction and operational cost. For this reason, the methodology for construction of low-cost thin client system is required. In the high-performance perspective, technologies for batch and real-time processing on the cluster of commodity machines are significant. As for the batch processing, one of the important applications is the high-performance parallel generation of segmented indexes for the distributed search system. The resource saving and performance improvement of the index generation and reconfiguration are strongly required. Furthermore, as a representative example of the real-time processing, the parallel rendering on the PC cluster is a significant application. As the image data has high resolution and fine-grained quality with a great number of polygons, it is essential to realize the high performance rendering of the large-scale three dimensional images. Based on this background, we address the following three iss

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SIFT特征分布式并行提取算法

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计算机研究与发展 2012年第5期49卷 1130-1141页

作者：姜桂圆张桂玲张大坤天津工业大学计算机科学与软件学院天津300387

SIFT(scale invariant feature transform)特征在物体检测和识别、图像配准与融合、纹理识别、场景分类、人脸检测、图像检索、三维重建、数字水印、影像追踪等领域具有广泛应用,但存在计算量大、消耗时间长的缺点.基于消息传递机制,采... 详细信息

SIFT(scale invariant feature transform)特征在物体检测和识别、图像配准与融合、纹理识别、场景分类、人脸检测、图像检索、三维重建、数字水印、影像追踪等领域具有广泛应用,但存在计算量大、消耗时间长的缺点.基于消息传递机制,采用数据并行策略,提出了在PC机群或COW(cluster ofworkstation)上提取图像SIFT特征的分布式并行算法(DP-SIFT算法):根据特征空间-高斯尺度金字塔的特点提出了高度宽度受限的数据块划分算法,设计了数据分配和特征调整方法;研究了数据块划分和数据发送方法对通信时间的影响,提出了基于消息传递机制的并行图像处理中数据块划分与数据发送方式协同对通信优化的策略;实验结果表明DP-SIFT算法具有良好的加速性能和较高的处理器利用效率,千兆以太网连接32核的PC机群系统图像规模为1024×768时,加速比和处理器效率分别可以达到20和0.6;图像规模为2048×1536时可达18和0.56.

关键词： SIFT DP—SIFT 数据并行消息传递并行图像处理数据分块

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Scheduling and Capacity Design in Overlay Computing Systems

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12th International Conference on Computational Science and Its Applications (ICCSA)

作者： Walkowiak, Krzysztof Kasprzak, Andrzej Kosowski, Michal Miziolek, Marek Wroclaw Univ Technol Dept Syst & Comp Networks Fac Elect PL-50370 Wroclaw Poland

ISBN: (纸本)9783642311277;9783642311284

parallel to new developments in the fields of computer networks and high performance computing, effective distributed systems have emerged to answer the growing demand to process huge amounts of data. Comparing to traditional network systems aimed mostly to send data, distributed computing systems are also focused on data processing what introduces additionally requirements in the system performance and operation. In this paper we assume that the distributed system works in an overlay mode, which enables fast, cost-effective and flexible deployment comparing to traditional network model. The objective of the design problem is to optimize task scheduling and network capacity in order to minimize the operational cost and to realize all computational projects assigned to the system. The optimization problem is formulated in the form of an ILP (Integer Linear Programming) model. Due to the problem complexity, four heuristics are proposed including evolutionary algorithms and Tabu Search algorithm. All methods are evaluated in comparison to optimal results yielded by the CPLEX solver. The best performance is obtained for the Tabu Search method that provides average results only 0.38% worse than optimal ones. Moreover, for larger problem instances with 20-minute limit of the execution time, the Tabu Search algorithm outperforms CPLEX for some cases.

关键词： distributed computing overlays ILP modeling optimization

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parallel training and testing methods for complex image processing algorithms on distributed, heterogeneous, unreliable, and non-dedicated resources

Parallel training and testing methods for complex image proc...

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Conference on parallel processing for Imaging Applications

作者： Usamentiaga, Ruben Garcia, Daniel F. Molleda, Julio Sainz, Ignacio Bulnes, Francisco G. Univ Oviedo Dept Comp Sci Gijon 33204 Asturias Spain

ISBN: (纸本)9780819484093

Advances in the image processing field have brought new methods which are able to perform complex tasks robustly. However, in order to meet constraints on functionality and reliability, imaging application developers often design complex algorithms with many parameters which must be finely tuned for each particular environment. The best approach for tuning these algorithms is to use an automatic training method, but the computational cost of this kind of training method is prohibitive, making it inviable even in powerful machines. The same problem arises when designing testing procedures. This work presents methods to train and test complex image processing algorithms in parallel execution environments. The approach proposed in this work is to use existing resources in offices or laboratories, rather than expensive clusters. These resources are typically non-dedicated, heterogeneous and unreliable. The proposed methods have been designed to deal with all these issues. Two methods are proposed: intelligent training based on genetic algorithms and PVM, and a full factorial design based on grid computing which can be used for training or testing. These methods are capable of harnessing the available computational power resources, giving more work to more powerful machines, while taking its unreliable nature into account. Both methods have been tested using real applications.

关键词： parallelization on unreliable non-dedicated resources parallel training parallel genetic algorithms image processing based on grid computing

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Exploiting parallelism in a X-ray Tomography Reconstruction Algorithm on Hybrid Multi-GPU and Multi-core Platforms

Exploiting Parallelism in a X-ray Tomography Reconstruction ...

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International Symposium on parallel and distributed processing with Applications, ISPA

作者： Ernesto Liria Daniel Higuero Monica Abella Claudia de Molina Manuel Desco Universidad Carlos III de Madrid Madrid Spain Hospital General Universitario Gregorio Marañón Madrid Spain

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 et al. Currently there are a strong need to speed-up the reconstruction of XRay CT data in order to extend its clinical applications. We present an efficient modular implementation of an FDK-based reconstruction algorithm that takes advantage of the parallel computing capabilities and the efficient bilinear interpolation provided by general purpose graphic processing units (GPGPU). The proposed implementation of the algorithm is evaluated for a high-resolution micro-CT and achieves a speed-up of 46, while preserving the reconstructed image quality.

关键词： Graphics processing unit Computed tomography image reconstruction parallel processing X-ray imaging Geometry Detectors

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Evaluation and comparison of cell nuclei detection algorithms

Evaluation and comparison of cell nuclei detection algorithm...

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IEEE 16th International Conference on Intelligent Engineering Systems, INES 2012

作者： Szénási, Sándor Vámossy, Zoltán Kozlovszky, Miklós Óbuda University Doctoral School of Applied Informatics Budapest Hungary Óbuda University John Von Neumann Faculty of Informatics Budapest Hungary MTA SZTAKI Laboratory of Parallel and Distributed Computing Budapest Hungary

ISBN: (纸本)9781467326957

The processing of microscopic tissue images and especially the detection of cell nuclei is nowadays done more and more using digital imagery and special immunodiagnostic software products. Since several methods (and applications) were developed for the same purpose, it is important to have a measuring number to determine which one is more efficient than the others. The purpose of the article is to develop a generally usable measurement number that is based on the "gold standard" tests used in the field of medicine and that can be used to perform an evaluation using any of image segmentation algorithms. Since interpreting the results themselves can be a pretty time consuming task, the article also contains a recommendation for the efficient implementation and a simple example to compare three algorithms used for cell nuclei detection. © 2012 IEEE.

关键词： image segmentation

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Reducing Application-level Checkpoint File Sizes: Towards Scalable Fault Tolerance Solutions

Reducing Application-level Checkpoint File Sizes: Towards Sc...

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International Symposium on parallel and distributed processing with Applications, ISPA

作者： iv'n Cores Gabriel Rodríguez María J. Martín Patricia Gonz'lez Computer Architecture Group University of A Coruña Spain Universidade da Coruna A Coruna Galicia ES

Systems intended for the execution of long-running parallel applications require fault tolerant capabilities, since the probability of failure increases with the execution time and the number of nodes. Checkpointing and rollback recovery is one of the most popular techniques to provide fault tolerance support. However, in order to be useful for large scale systems, current checkpoint-recovery techniques should tackle the problem of reducing checkpointing cost. This paper addresses this issue through the reduction of the checkpoint file sizes. Different solutions to reduce the size of the checkpoints generated at application level are proposed and implemented in a checkpointing tool. Detailed experimental results on two multicore clusters show the effectiveness of the proposed methods.

关键词： Checkpointing Arrays Optimization Fault tolerance Fault tolerant systems Libraries Multicore processing

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The Web-Based Assessment for Inundated Area Detection

The Web-Based Assessment for Inundated Area Detection

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ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and parallel/distributed Computing (SNPD)

作者： Ponthip Limlahapun Hiromichi Fukui Keio Research Institute Keio University Kanagawa Japan Chubu Institute for Advanced Studies Professor Director of International Digital Earth Applied Science Research Center (IDEAS) Chubu University Aichi Japan

An object-based image processing technique is applied to detect inundated areas using Land sat images. An interoperable Web-based system was developed to conduct the analyses so that redundant steps in Land sat image processing can be effectively eliminated. A review process is used to discover and develop suitable algorithms to automatically detect inundated areas and immediately transfer the results to the Web-based interface. This is a significant improvement over currently available methods for inundation detection systems. The tool is expected to be a practical inundated area detection function and be applicable across wide-reaching areas.

关键词： Satellites Feature extraction image segmentation Remote sensing MATLAB Earth

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A Novel Approach for Regularized Signal Deconvolution Based on Hybrid Swarm Intelligence: Application to Neutron Radiography

A Novel Approach for Regularized Signal Deconvolution Based ...

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

作者： Slami Saadi Abderrezak Guessoum Maamar Bettayeb Department of Electronics University Ziane Achour Djelfa Algeria Department of Electronics LATSI Laboratory University Saad Dahlab Burgas Algeria Department of Electrical and Computer Engineering University of Sharjah UAE

In this work, we introduce a new approach for the signal deconvolution problem, which is useful for the enhancement of neutron radiography projections. We attempt to restore original signals and get rid of noise present during acquisition or processing, due to gamma radiations or randomly distributed neutron flux. Signal deconvolution is an ill-posed inverse problem, so regularization techniques are used to smooth solutions by imposing constraints in the objective function. Various popular algorithms have been developed to solve such problem. This paper proposes a new approach to the nonlinear degraded signals restoration which is useful in many signal enhancement applications, based on a synergy of two swarm intelligence algorithms: particle swarm optimization (PSO) and bacterial foraging optimization (BFO) applied for total variation (TV) minimization, instead of the standard Tikhonov regularization method. We attempt to reconstruct or recover signals using some a priori knowledge of the degradation phenomenon. The truncated singular value decomposition and the wavelet filtering methods are also considered in this paper. A comparison between several powerful techniques is conducted.

关键词： Noise Microorganisms image restoration Deconvolution Optimization Nonlinear filters

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