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检索条件"任意字段=Conference on Parallel and Distributed Methods for Image Processing"

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Fast Estimation of Gaussian Mixture Model Parameters on GPU Using CUDA

Fast Estimation of Gaussian Mixture Model Parameters on GPU ...

引用

IEEE International conference on parallel and distributed Computing, Applications and Technologies (PDCAT)

作者： Lukas Machlica Jan Vanek Zbynek Zajic Department of Cybernetics University of West Bohemia Pilsen Czech Republic

Gaussian Mixture Models (GMMs) are widely used among scientists e.g. in statistics toolkits and data mining procedures. In order to estimate parameters of a GMM the Maximum Likelihood (ML) training is often utilized, more precisely the Expectation-Maximization (EM) algorithm. Nowadays, a lot of tasks works with huge datasets, what makes the estimation process time consuming (mainly for complex mixture models containing hundreds of components). The paper presents an efficient and robust implementation of the estimation of GMM statistics used in the EM algorithm on GPU using NVIDIA's Compute Unified Device Architecture (CUDA). Also an augmentation of the standard CPU version is proposed utilizing SSE instructions. Time consumptions of presented methods are tested on a large dataset of real speech data from the NIST Speaker Recognition Evaluation (SRE) 2008. Estimation on GPU proves to be more than 400 times faster than the standard CPU version and 130 times faster than the SSE version, thus a huge speed up was achieved without any approximations made in the estimation formulas. Proposed implementation was also compared to other implementations developed by other departments over the world and proved to be the fastest (at least 5 times faster than the best implementation published recently).

关键词： Vectors Graphics processing unit Instruction sets Kernel Estimation Memory management Indexes

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PHASE SPACE ANALYSIS OF THE HARMONIC OSCILLATOR WITH LEVY NOISE: SPECTRAL MEASURE AND DEVIATION FROM ELLIPTICITY

PHASE SPACE ANALYSIS OF THE HARMONIC OSCILLATOR WITH LEVY NO...

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European Signal processing conference

作者： Steeve Zozor Christophe Vignat GIPSA-Lab Departement Image et Signal LTHI Ecole Polytechnique Federale de Lausanne

We show that the location and velocity of the harmonic oscillator with Levy-stable noise are mutually Levy-stable distributed. We give explicitly the associated spectral measure, exhibiting both the non independence a... 详细信息

关键词： Vectors Oscillators Harmonic analysis Noise Joints Density measurement Approximation methods

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Efficient image Denoising by MRF Approximation with Uniform-Sampled Multi-spanning-tree

Efficient Image Denoising by MRF Approximation with Uniform-...

引用

International conference on image and Graphics (ICIG)

作者： Jun Sun Hongdong Li Xuming He National ICT Australia Australian National University Canberra Australia Australian National University Canberra Australia NICTA Canberra Australia

Traditionally, image processing based on Markov Random Field (MRF) is often addressed on a 4-connected grid graph defined on the image. This structure is not computationally efficient. In our work, we develop a multiple-trees structure to approximate the 4-connected grid. A set of spanning trees are generated by a new algorithm: re-weighted random walk (RWRW). This structure effectively covers the original grid and guarantees uniformly distributed occurrence of each edge. Exact maximum a posterior (MAP) inference is performed on each tree structure by dynamic programming and a median filter is chosen to merge the results together. As an important application, image denoising is used to validate our method. Experimentally, our algorithm provides better performance and higher computational efficiency than traditional methods (such as Loopy Belief Propagation) on a 4-connected MRF.

关键词： image edge detection PSNR Inference algorithms Approximation algorithms Merging image denoising

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GPU Implementation of a Deformable 3D image Registration Algorithm

GPU Implementation of a Deformable 3D Image Registration Alg...

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Annual International conference of the IEEE Engineering in Medicine and Biology Society

作者： Hamed Mousazadeh Bahram Marami Shahin Sirouspour Alexandru Patriciu School of Biomedical Engineering McMaster University Department of Electrical and Computer Engineering McMaster University

ISBN: (纸本)9781424441211

We present a parallel implementation of a new deformable image registration algorithm using the Computer Unified Device Architecture (CUDA). The algorithm co-registers preoperative and intraoperative 3-dimensional magnetic resonance (MR) images of a deforming organ. It employs a linear elastic dynamic finite-element model of the deformation and distance measures such as mutual information and sum of squared differences to align volumetric image data sets. Computationally intensive elements of the method such as interpolation, displacement and force calculation are significantly accelerated using a Graphics processing Unit (GPU). The result of experiments carried out with a realistic breast phantom tissue shows a 37-fold speedup for the GPU-based implementation compared with an optimized CPU-based implementation in high resolution MR image registration. The GPU implementation is capable of registering 512×512×136 image sets in just over 2 seconds, making it suitable for clinical applications requiring fast and accurate processing of medical images.

关键词： Graphics processing unit Three dimensional displays Mathematical model image registration Equations Finite element methods Vectors

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Informatics Engineering and Information Science, Part II 2011

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丛书名： Communications in Computer and Information Science

2011年

作者： Azizah Abd Manaf Akram Zeki Mazdak Zamani Suriayati Chuprat Eyas El-Qawasmeh

ISBN: (数字)9783642254536

ISBN: (纸本)9783642254529

This 4-Volume-Set, CCIS 0251 - CCIS 0254, constitutes the refereed proceedings of the International conference on Informatics Engineering and Information Science, ICIEIS 2011, held in Kuala Lumpur, Malaysia, in November 2011. The 210 revised full papers presented together with invited papers in the 4 volumes were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on e-learning, information security, software engineering, image processing, algorithms, artificial intelligence and soft computing, e-commerce, data mining, neural networks, social networks, grid computing, biometric technologies, networks, distributed and parallel computing, wireless networks, information and data management, web applications and software systems, multimedia, ad hoc networks, mobile computing, as well as miscellaneous topics in digital information and communications.

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Informatics Engineering and Information Science, Part III 2011

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丛书名： Communications in Computer and Information Science

2011年

作者： Azizah Abd Manaf Shamsul Sahibuddin Rabiah Ahmad Salwani Mohd Daud Eyas El-Qawasmeh

ISBN: (数字)9783642254628

ISBN: (纸本)9783642254611

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Biomedical image processing with GPGPU using CUDA

Biomedical image processing with GPGPU using CUDA

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Proceedings of the International Convention MIPRO

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

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.

关键词： Graphics processing unit Instruction sets image processing Kernel Optimization Memory management Pixel

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Set Utilization Based Dynamic Shared Cache Partitioning

Set Utilization Based Dynamic Shared Cache Partitioning

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International conference on parallel and distributed Systems (ICPADS)

作者： Peter Deayton Chung-Ping Chung Department of Computer Science National Chiao-Tung University Hsinchu Taiwan

As the number of processors sharing a cache increases, conflict misses due to interference amongst competing processes have an increasing impact on the individual performance of processes. Cache partitioning is a method of allocating a cache between concurrently executing processes in order to counteract the effects of inter-process conflicts. However, cache partitioning methods commonly divide a shared cache into private partitions dedicated to a single processor, which can lead to underutilized portions of the cache when set accesses are non-uniform. Our proposed method compliments these cache partitioning algorithms by creating an additional shared partition able to be shared amongst all processors. Underutilized areas of the cache are identified by a monitoring circuit and used for the shared partition. Detection of underutilization is based on the number of unique set accesses for a given allocated way. For a 16-way set associative cache, the implementation of our method requires 64 bytes of storage overhead per core in addition to that needed for the method that determines the sizes of the private partitions. For the tested system, our method is able to improve performance over the traditional LRU policy for a number of selected benchmark sets by an average of 1.4% and up to 13.3% for a two core system and an average of 1.4% and up to 7.8% for a four core system, and is able to improve the performance of a conventional cache partitioning method (Utility-Based Cache Partitioning) by an average of 0.1% and up to 0.5% for both a two and four core systems.

关键词： Benchmark testing Partitioning algorithms Program processors Monitoring Multicore processing Classification algorithms Cost function

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A robust digital image watermarking using transformation domain and evolutionary computation techniques

A robust digital image watermarking using transformation dom...

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International conference on Machine Learning and Cybernetics (ICMLC)

作者： Chih-Chin Lai Hsin-Chih Chen Geng-Ming Yeh Chen-Sen Ouyang Department of Electrical Engineering National University of Kaohsiung Kaohsiung Taiwan Department of Information Engineering I-Shou University Kaohsiung Taiwan

With the rapid expansion of Internet and distributed technology, multimedia security and digital rights management have been received much attention in the literature, As a major method for intellectual property right protecting, digital watermarking techniques have been widely studied and used. Extensive algorithms have been proposed for digital images. In this paper, a robust digital image watermarking scheme which applies the common transformation domain methods and evolutionary computation technique is presented. The experimental results show that the proposed scheme is robust to several common image-processing attacks, and has good perceptual quality at the same time.

关键词： Evolutionary computation Discrete wavelet transforms PSNR image coding Transform coding Helium

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A Hadoop solution for ballistic image analysis and recognition

A Hadoop solution for ballistic image analysis and recogniti...

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International conference on High Performance Computing & Simulation (HPCS)

作者： Hakan Kocakulak Tugba Taskaya Temizel Space Technologies Research Institute Turkish Science and Technology Research Council Ankara Turkey Informatics Institute Information Systems Department Middle East Technical University Ankara Turkey

The importance of ballistic applications has been recently recognized due to the increasing crime and terrorism threats and incidents around the world. Ballistic image analysis is one of the application areas which requires immediate response with high precision from large databases. Here, the microscopic markings on cartridge case of a bullet obtained in a crime scene are compared with that of images on ballistic databases for similarity in order to find out whether it is fired from any of the firearms within the database. In this paper, we have implemented a MapReduce solution using Hadoop for ballistic image comparison which is a high data and computation intensive task. MapReduce, a programming model developed by Google, provides a scalable, flexible and QoS guaranteed IT infrastructure particularly for embarrassingly parallel data oriented computational tasks. Our results have shown that we can effectively utilize the computing resources and gain significant increases in performance. Furthermore, we will share our experiences in programming and tuning a Hadoop cluster in the paper.

关键词： Correlation Central processing Unit Computers distributed databases Graphics Java Software

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