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检索条件"任意字段=Conference on Parallel Processing for Imaging Applications"

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Fast Bridgeless Pyramid Segmentation for Organized Point Clouds 16

Fast Bridgeless Pyramid Segmentation for Organized Point Clo...

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16th International Joint conference on Computer Vision, imaging and Computer Graphics Theory and applications (VISIGRAPP) / 16th International conference on Computer Vision Theory and applications (VISAPP)

作者： Madaras, Martin Stuchlik, Martin Talcik, Matus Skeletex Res Bratislava Slovakia Comenius Univ Fac Math Phys & Informat Bratislava Slovakia Masaryk Univ Brno Brno Czech Republic

ISBN: (纸本)9789897584886

An intelligent automatic robotic system needs to understand the world as fast as possible. A common way to capture the world is to use a depth camera. The depth camera produces an organized point cloud that later needs to be processed to understand the scene. Usually, segmentation is one of the first preprocessing steps for the data processing pipeline. Our proposed pyramid segmentation is a simple, fast and lightweight split-and-merge method designed for depth cameras. The algorithm consists of two steps, edge detection and a hierarchical method for bridgeless labeling of connected components. The pyramid segmentation generates the seeds hierarchically, in a top-down manner, from the largest regions to the smallest ones. The neighboring areas around the seeds are filled in a parallel manner, by rendering axis-aligned line primitives, which makes the performance of the method fast. The hierarchical approach of labeling enables to connect neighboring segments without unnecessary bridges in a parallel way that can be efficiently implemented using CUDA.

关键词： Point Cloud Segmentation parallel Pyramid GPU CUDA

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parallel Computation of Mutual Information in Multicore Environment & Its applications in Medical Image Registration

Parallel Computation of Mutual Information in Multicore Envi...

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International conference on Medical imaging, M-Health and Emerging Communication Systems (MedCom)

作者： Saxena, Sanjay Sharma, Shiru Sharma, Neeraj Indian Inst Technol BHU Sch Biomed Engn Varanasi Uttar Pradesh India

ISBN: (纸本)9781479950973

Mutual information (MI) is the measure of amount of information containing by one random variable about another. It is an established similarity measure used for image registration. Calculation of mutual information is very computationally meticulous and time consuming at the time of computation of the immense images or at the time of processing with set of images. Main purpose of this research work is to propose a proficient method to compute mutual information used for image registration using parallel computing. This method is able to work with different numbers of threads to take all the benefits of the processors having multiple cores like core i3, core i5, core i7 after maintaining the synchronization between cores. Our experiment shows the significant speed up using easily available multi core architectures especially for core i7 processor. Another major purpose of this paper is to describe the application of the parallel computation of mutual information in image registration especially in the case of medical image registration like CT (Computed Tomography) - PET (Positron Emission Tomography) and Other modalities of Neuroimaging.

关键词： Mutual Information parallel Computing Image Registration Medical imaging Core CT PET

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Computation of morphological texture features for medical imaging applications

Computation of morphological texture features for medical im...

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Medical imaging 1998 conference on Image processing

作者： Patel, MJ Kehtarnavaz, N Dougherty, ER Batman, S Sivakumar, K Popov, AT Texas A&M Univ Dept Elect Engn Comp Aided Med Diagnost Imaging Lab College Stn TX 77843 USA

ISBN: (纸本)0819427837

Texture is an important attribute which is widely used in various image analysis applications. Among texture features, morphological texture features are least utilized in medical image analysis. From a computational standpoint, extracting morphological texture features from an image is a challenging task. The computational problem is made even greater in medical imaging applications where large images such as mammograms are to be analyzed. This paper discusses an efficient method to compute morphological texture features for any geometry of a structuring element corresponding to a texture type. A benchmarking of the code on three machines (Sun SPARC 20, Pentium II based Dell 400 workstation, and SGI Power Challenge 10000XL) as well as a parallel processing implementation was performed to obtain an optimum processing configuration. A sample processed mammogram is shown to illustrate the code outcome.

关键词： morphological texture feature computation grey-scale granulometry computation mammography texture analysis hardware benchmarking

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Multi-kernel Ray Traversal for Graphics processing Units

Multi-kernel Ray Traversal for Graphics Processing Units

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International Joint conference on Computer Vision, imaging and Computer Graphics Theory and applications (VISIGRAPP)

作者： Schiffer, Thomas Fellner, Dieter W. Graz Univ Technol Inst Comp Graph & Wissensvisualisierung Graz Austria Tech Univ Darmstadt Darmstadt Germany Fraunhofer IGD Darmstadt Germany

ISBN: (纸本)9783319251172;9783319251165

Ray tracing is a very popular family of algorithms that are used to compute images with high visual quality. One of its core challenges is designing an efficient mapping of ray traversal computations to massively parallel hardware architectures like modern algorithms graphics processing units (GPUs). In this paper we investigate the performance of state-of-the-art ray traversal algorithms on GPUs and discuss their potentials and limitations. Based on this analysis, a novel ray traversal scheme called batch tracing is proposed. It subdivides the task into multiple kernels, each of which is designed for efficient parallel execution. Our algorithm achieves comparable performance to current approaches and represents a promising direction for future research.

关键词： Ray tracing SIMT parallelism Graphics processing units

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parallel VLSI Architectures for High-Throughput Image processing in Medical imaging 5

Parallel VLSI Architectures for High-Throughput Image Proces...

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5th International conference on Innovative Data Communication Technologies and Application, ICIDCA 2024

作者： Vinayagam, P. Yuvaraaj, R. Sathiyanandham, S. Kanagamalliga, S. Saveetha Engineering College Chennai602105 India

The need for efficient and reliable image processing techniques has never been greater in medical imaging. The proposed work analyzes and designs parallel VLSI (Very Large-Scale Integration) architectures that meet the stringent demands of high-throughput medical image processing. The remainder of the paper is organized as follows, beginning with a discussion of the computational challenges that arise organically in medical imaging and why it is crucial to surmount these obstacles. The section on the proposed work describes the architecture, parallelization strategies, and processing pipeline, providing context for the hardware and Software underlying the system. The evaluation results below demonstrate significant enhancements in processing speed and image quality. Due to their real-time capabilities and high efficiency, parallel VLSI architectures have the potential to revolutionize medical image processing, resulting in more accurate diagnoses and more effective treatments. Research into optimizing these structures and discovering new applications is anticipated to result in further advances in medical imaging. © 2024 The Authors. Published by Elsevier B.V.

关键词： Medical imaging

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High speed embedded imaging architectures for multichannel imaging

High speed embedded imaging architectures for multichannel i...

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imaging Systems and applications, ISA 2013

作者： Schwannecke, Hans-Christian Rosenberger, Maik Schellhorn, Mathias Linß, Gerhard University of Technology Ilmenau Department Quality assurance and Industrial Image Processing Embedded Systems Group Gustav Kirchhoff Platz 2 98693 Ilmenau Germany

Multichannel imaging is a key technology for new application fields. Therefore a new parallel image processing architecture was designed. The new platform allows fast processing speed and solves problems in multispect... 详细信息

ISBN: (纸本)9781557529756

关键词： imaging systems

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Fast processing of quantitative phase profiles from off-axis interferograms for real-time applications 1

Fast processing of quantitative phase profiles from off-axis...

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1st conference on Quantitative Phase imaging (QPI)

作者： Girshovitz, Pinhas Shaked, Natan T. Tel Aviv Univ Dept Biomed Engn Fac Engn IL-69978 Tel Aviv Israel

ISBN: (纸本)9781628414264

We review new and efficient algorithms, lately presented by us, 1,2 for rapid reconstruction of quantitative phase maps from off-axis digital interferograms. These algorithms improve the conventional Fourier-based algorithm by using the Fourier transforms and the phase unwrapping process more efficiently, and thus decrease the calculation complexity required for extracting the sample phase map from the recorded interferograms. Using the new algorithms, on a standard personal computer without using the graphic processing-unit programming or parallel computing, we were able to speed up the processing and reach frame rates of up to 45 frames per second for one megapixel off-axis interferograms. These capabilities allow real-time visualization, calculation and data extraction for dynamic samples and processes, inspected by off-axis digital holography. Specific applications include biological cell imaging without labeling and real-time nondestructive testing.

关键词： quantitative phase imaging real-time imaging interferometry digital holography

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Distributed and parallel Subarray Beamforming for Underwater Real-Time 3-D Acoustic imaging

Distributed and Parallel Subarray Beamforming for Underwater...

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2nd International conference on Computer Science and Network Technology (ICCSNT)

作者： Han, Yeqiang Zhou, Fan Tian, Xiang Chen, Yaowu Zhejiang Univ Inst Adv Digital Technol & Instrumentat Hangzhou 310003 Zhejiang Peoples R China

ISBN: (纸本)9781467329644;9781467329637

In this paper, we propose a distributed and parallel subarray beamforming (DPS) algorithm for performing underwater real-time 3-D acoustic imaging. The principle idea of this algorithm is that the full populated sensor array is subdivided into two stage distributed subarrays and the beamforming is carried out in parallel for each stage subarray. The proposed algorithm overcomes the problems of massive computational load affecting the engineering applications of the conventional beamforming techniques, while achieving the similar resolutions. The memory requirement obtained with the proposed algorithm is reduced by four orders of magnitude and the computational requirement is reduced by two orders of magnitude when compared with the conventional beamforming (CBF). The simulation and the comparisons illustrate the results and the efficiency of the algorithm.

关键词： Underwater 3-D acoustic imaging sonar sensor array system sonar signal processing distributed and parallel subarray beamforming conventional beamforming

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A Modified parallel Thinning Method for Handwritten Oriya Character Images 4th

A Modified Parallel Thinning Method for Handwritten Oriya Ch...

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4th International conference on Frontiers in Intelligent Computing - Theory and applications (FICTA)

作者： Bag, Soumen Chawpatnaik, Glory ISM Dhanbad Dept Comp Sci & Engn Dhanbad Bihar India IIIT Bhubaneswar Dept Comp Sci & Engn Bhubaneswar Orissa India

ISBN: (纸本)9788132226956;9788132226932

Binary image thinning has wide applications in image processing, machine vision, and pattern recognition. Thinning is a preprocessing step to obtain single-pixel-thin skeleton for document imaging and pattern analysis. Indian languages are complex in character shape than Latin, Chinese, Japanese, and Korean languages. The performance of existing thinning methods cannot reach the state of the art in the field of document image processing for Indian languages. Our objective is to improve the performance of complex-shaped character skeletonization, particularly for Oriya script. This paper presents an iterative parallel thinning method which is well suited to handwritten Oriya characters. Some fundamental requirements of thinning like preservation of stroke connectivity, removal of spurious strokes have been ensured in this method. Experimental results show its efficacy comparing with other existing thinning methods.

关键词： Elimination rule Handwritten Oriya script OCR parallel thinning Template Skeleton

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Noise removal of the X-ray medical image using fast spatial filters and GPU 41

Noise removal of the X-ray medical image using fast spatial ...

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conference on applications of Digital Image processing XLI

作者： Cadena, Luis Zotin, Alexander Cadena, Franklin Espinosa, Nikolai Univ Fuerzas Armadas ESPE Ave Gral Ruminahui S-N Sangolqui Ecuador Reshetnev Siberian State Univ Sci & Technol 31 Krasnoyarsky Rabochy Pr Krasnoyarsk 660037 Russia Coll Juan Suarez Chacon Quito Ecuador

ISBN: (数字)9781510620766

ISBN: (纸本)9781510620766

Medical images are corrupted by different types of noises caused by the equipment itself. It is very important to obtain precise images to facilitate accurate observations for the given application. Removing of noise from images is now a very challenging issue in the field of medical image processing. This work undertake the study of noise removal techniques in medical image by using fast implementation of different digital filters, such as average, median and Gaussian filter. processing of X-ray medical images takes a significant time. Now days modern hardware allows to use parallel technology for image processing on CPU and GPU. Using GPU processing technology were proposed parallel implementations of noise reduction algorithm taking into account the data parallelism. The experimental study conducted on medical X-ray image, so that to choose the best filters considering medical task and time of processing. The comparison of the implementation of fast filters algorithm and GPU implementation show great increase in performance. Graphics processing units (GPUs) are used today in a wide range of applications, mainly because they can dramatically accelerate parallel computing. In the field of medical imaging, GPUs are in some cases crucial for enabling practical use of computationally demanding algorithms.

关键词： medical image average fast filter median fast filter Gaussian fast filter parallel programming GPU

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