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Load balancing methods for ray tracing and binary tree computing using PVM

parallel COMPUTING 1995年第12期21卷 1963-1978页

作者： Sekharan, CN Goel, V Sridhar, R UNIV CENT FLORIDA DEPT COMP SCIORLANDOFL 32816 UNIV OKLAHOMA SCH COMP SCINORMANOK 73019

We propose efficient load balancing methods for two computational problems namely ray tracing and bottom-up binary tree computing in a distributed environment. In the context of ray tracing, we propose a variant of a static load balancing technique presented in [15] where the sampling is based on partitioning the object space. Our approach partitions the image instead and uses an efficient scheduling technique for load balancing. Computations carried out on a binary tree arise naturally in image processing and network optimization problems. Many of these problems are solved efficiently in parallel by the popular tree contraction technique [1]. In this paper, we explore the tree-contraction technique in a distributed setting using the grain packing method [9]. Implementations of our algorithms on a cluster of workstations using parallel Virtual Machine (PVM) [6] demonstrate near-perfect load balancing.

关键词： load balancing ray tracing binary tree distributed environment PVM workstation cluster

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distributed image processing on spiral architecture 5

Distributed image processing on spiral architecture

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5th International conference on Algorithms and Architectures for parallel processing

作者： Wu, Q He, XJ Hintz, T Univ Technol Sydney Dept Comp Syst Sydney NSW 2007 Australia

ISBN: (纸本)0769515126

Improving the computation efficiency is a key issue in image processing, especially in edge detection, because edge detection is very computationally intensive. With the development of real-time application of image processing, fast processing response is becoming more critical. In this paper, a technique for distributed image processing on Spiral Architecture is proposed, which provides a platform for speeding up image processing based on clusters.

关键词： spiral architecture distributed processing image processing client-server model

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Simulation of parallel processing for distributed Multi-Target Tracking in Smart Camera Networks 16

Simulation of Parallel Processing for Distributed Multi-Targ...

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10th International conference on distributed Smart Cameras (ICDSC)

作者： Jafarizadeh, Mehdi YadollahPour, Naeeme Shahid Beheshti Univ Comp Engn Dept Tehran Iran Univ Tehran Dept Management & Accounting Tehran Iran

ISBN: (纸本)9781450347860

In order to reduce the real-time processing gap of distributed algorithms on smart camera networks, we have evaluated a parallel processing method which exploits the processing capabilities of free cameras as auxiliary for busy ones. The communication infrastructure or camera processing capabilities are not included in the traditional evaluation methods like datasets or even virtual reality tools, so they are not suitable to analyze the complexity of distributed algorithms. For this purpose, we have developed a modular framework based on OMNET++ simulation environment named CAM-DIST, in which the velocity model of soccer players are emulated. Simulation results show that parallel processing improves overall efficiency, but could have side effects on individual camera estimations;so choosing optimal sharing value and destinations will enhance the performance.

关键词： Smart camera networks OMNET plus complexity analysis of distributed algorithms

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Block rotation: Implementation and applications

Block rotation: Implementation and applications

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conference on parallel and distributed methods for image processing

作者： Fatemi, O Panchanathan, S Univ. of Ottawa (Canada) Univ. of Ottawa (United States)

ISBN: (纸本)0819425885

Visual media processing is becoming increasingly important because of the wide variety of image and video based applications. Block rotation is an important operation in different image/video processing tasks such as graphics, fractal processing, pattern matching and image registration. Remote sensing, medical imaging, computer vision, computer graphics, and video coding are typical applications of digital image rotation. However, a hardware implementation of the block rotation algorithm has not been realized and software implementation is slow. Hence, they are not suitable for real-time execution. In this paper, we propose a novel method for block rotation, which is fast and suitable for hardware implementation. The algorithm employs area based interpolation. Experimental results have shown the performance enhancement compared to classical interpolation algorithms at a similar level of complexity.

关键词： image rotation spatial transformation affine transform interpolation forward mapping and backward mapping

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oRis: Multiagents approach for image processing

oRis: Multiagents approach for image processing

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SPIE conference on parallel and distributed methods for image processing II

作者： Rodin, V Harrouet, F Ballet, P Tisseau, J Technopole Brest Iroise Ecole Natl Ingn Brest F-29608 Brest France

ISBN: (纸本)0819429074

In this article, we present a parallel image processing system based on the concept of reactive agents. This means that, in our system, each agent has a very simple behavior which allows it to take a decision (find out an edge, a region,...) according to its position in the image and to the information enclosed in it. Our system lies in the oRis language, which allows to describe very finely and simply the agents' behaviors. In fact, oRis is an interpreted and dynamic multiagent language. First of all, oRis is an object language with the use of classes regrouping attributes and methods. The syntax is close to the CSS language and includes notions of multiple inheritance, oRis is also an agent language: every object with a method 'main()' becomes an agent. This method is cyclically executed by the system scheduler and corresponds to the agent behavior. We also present an application made with oRis. This application allows to detect concentric striae located on different natural "objects" (age-rings of tree, fish otolith growth rings, striae of some minerals,...). The stopping of the multiagent system is implemented through a technique issued from immunology: the apoptosis.

关键词： multiagent language multiagent system parallel image processing reactive agents striae detection

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A fast and fully distributed method for region-based image segmentation Fast distributed region-based image segmentation

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JOURNAL OF REAL-TIME image processing 2021年第3期18卷 793-806页

作者： Mazouzi, Smaine Guessoum, Zahia Skikda Univ 20 Aout 1955 Comp Sci Dept Skikda Algeria Univ Reims Sorbonne Univ CReSTIC Reims Lip6 Paris France

distributed and parallel computing techniques allow fast image processing, namely when these techniques are applied at the low and the medium level of a vision system. In this paper, a collective and distributed method for image segmentation is introduced and evaluated. The method is modeled as a multi-agent system, where the agents aim to collectively produce a region-based segmentation. Each agent starts searching for an acceptable region seed by randomly jumping within the image. Next, it performs a region growing around its position. Thus, several agents find themselves within the same homogeneous region and are organized in a graph where two agents are connected if they are within the same region. So, a unifying of the labels in a same region is collaboratively performed by the agents themselves. The proposed method was experimented on real range images from the ABW dataset and the Object Segmentation Database (OSD) one, and the obtained results were compared to those of some well-referenced methods from the literature. The evaluation results show that the proposed method provides fast and accurate image segmentation, allowing it to be deployed for real-time vision systems.

关键词： image segmentation Region growing Pixel labeling distributed computing Real-time computer vision systems

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A Multi-granularity parallel Model for Unified Remote Sensing image processing WebServices

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TRANSACTIONS IN GIS 2012年第6期16卷 845-866页

作者： Guo, Wei Zhu, Xinyan Hu, Tao Fan, LiWei Wuhan Univ State Key Lab Informat Engn Surveying Mapping & R LIESMARS Wuhan 430079 Peoples R China

The growth of the Web has resulted in the Web-based sharing of distributed geospatial data and computational resources. The Geospatial processing Web (GeoPW) described here is a set of services that provide a wide array of geo-processing utilities over the Web and make geo-processing functionalities easily accessible to users. High-performance remote sensing image processing is an important component of the GeoPW. The design and implementation of high-performance image processing are, at present, an actively pursued research topic. Researchers have proposed various parallel strategies for single image processing algorithm, based on a computer science approach to parallel processing. This article proposes a multi-granularity parallel model for various remote sensing image processing algorithms. This model has four hierarchical interfaces that are labeled the Region of Interest oriented (ROI-oriented), Decompose/Merge, Hierarchical Task Chain and Dynamic Task interfaces or sub-models. In addition, interfaces, definitions, parallel task scheduling and fault-tolerance mechanisms are described in detail. Based on the model and methods, we propose an open-source online platform named OpenRS-Cloud. A number of parallel algorithms were uniformly and efficiently developed, thus certifying the validity of the multi-granularity parallel model for unified remote sensing image processing web services.

关键词： REMOTE-sensing images image processing WEB services parallel programs (Computer programs) GEOSPATIAL data GEOGRAPHIC information systems

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parallel image encryption with bitplane decomposition and genetic algorithm

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MULTIMEDIA TOOLS AND APPLICATIONS 2018年第19期77卷 25799-25819页

作者： Mozaffari, Saeed Semnan Univ Fac Elect & Comp Engn Semnan Iran

image encryption is an efficient technique to protect image content from unauthorized parties. In this paper a parallel image encryption method based on bitplane decomposition is proposed. The original grayscale image is converted to a set of binary images by local binary pattern (LBP) technique and bitplane decomposition (BPD) methods. Then, permutation and substitution steps are performed by genetic algorithm (GA) using crossover and mutation operations. Finally, these scrambled bitplanes are combined together to obtain encrypted image. Instead of random population selection in GA, a deterministic method with security keys is utilized to improve security level. The proposed encryption method has parallel processing capability for multiple bitplanes encryption. This distributed GA with multiple populations increases encryption speed and makes it suitable for real-time applications. Simulations and security analysis are done to demonstrate efficiency of our algorithm.

关键词： parallel image encryption Bitplain decomposition Local binary pattern Metaheuristic algorithms parallel genetic algorithm GPU programming

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Pipelining parallel image compositing and delivery for efficient remote visualization

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JOURNAL OF parallel AND distributed COMPUTING 2009年第3期69卷 230-238页

作者： Wu, Qishi Gao, Jinzhu Chen, Zizhong Zhu, Mengxia Univ Memphis Dept Comp Sci Memphis TN 38152 USA Univ Pacific Dept Comp Sci Stockton CA 95211 USA Colorado Sch Mines Dept Math & Comp Sci Golden CO 80401 USA So Illinois Univ Dept Comp Sci Carbondale IL 62901 USA

Scientific datasets of large volumes generated by next-generation computational sciences need to be transferred and processed for remote visualization and distributed collaboration among a geographically dispersed team of scientists. parallel visualization using high-performance computing facilities is a typical approach to processing such increasingly large datasets. We propose an optimized image compositing scheme with linear pipeline and adaptive transport to support efficient image delivery to a remote client. The proposed scheme arranges an arbitrary number of parallel processors within a cluster in a linear order and divides the image into a carefully selected number of segments, which flow through the linear incluster pipeline and wide-area networks to the remote client consecutively. We analytically determine the segment size that minimizes the final image display time and derive the conditions where the proposed image compositing and delivery scheme outperforms the traditional schemes including the binary swap algorithm. In order to match the transport throughput for image delivery over wide-area networks to the pipelining rate for image compositing within the cluster, we design a class of transport protocols using stochastic approximation methods that are able to stabilize the data flow at a target rate. The experimental results from remote visualization of large-scale scientific datasets justify the correctness of our theoretical analysis and illustrate the superior performances of the proposed method. (C) 2008 Elsevier Inc. All rights reserved.

关键词： image compositing Pipelining Transport control Remote visualization parallel and distributed systems

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Contract-Linda: A paradigm for programming heterogeneous parallel systems

Contract-Linda: A paradigm for programming heterogeneous par...

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conference on parallel and distributed methods for image processing

作者： Pycock, D Jackson, RO Univ. of Birmingham (United Kingdom)

ISBN: (纸本)0819425885

Contract-Linda is a novel programming architecture for heterogeneous parallel machines particularly suited to image processing. Previous research has concentrated on static and pre-determined scheduling of computation and on fine grain parallelism. Pre-determined scheduling is satisfactory in cases where the computational process is fully deterministic. However with many image interpretation schemes the flow of control and the nature of the computational procedures can only be determined at run-time. In this paper we describe a programming paradigm for coarse grain and task level parallelism. Task management is based on the Contract Net protocol and utilises the Linda. Coordination Language to provide run-time scheduling. This paradigm accommodates a closely coupled network of heterogeneous processing modules which differ greatly in computational capability;modules based on neural networks, semantic networks, vector and scalar processors are accommodated. Contract;Linda allo-cvs specialised heterogeneous machines to be exploited using a straightforward generic programming model. It does this by providing an internal task management mechanism which ensures that the heterogeneous processing elements are used by the tasks most suited to them and exploits dynamic parallelism within the problem as it is solved. By separating the task of describing the problem from that of describing how the work is carried out on the machine (and providing a solution for this problem) we allow applications to be quickly developed which can effectively utilise specialised machines without the need for specialised programming. We report an experiment to re-implement a cell image interpretation system using Contract-Linda.

关键词： heterogeneous computing parallel computing distributed artificial intelligence image interpretation

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