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检索条件"主题词=Parallel Image Processing"

共 76 条记录，以下是51-60 订阅

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parallel Region-Based Level Set Method with Displacement Correction for Tracking a Single Moving Object

Parallel Region-Based Level Set Method with Displacement Cor...

引用

11th International Conference on Advanced Concepts for Intelligent Vision Systems

作者： Fei, Xianfeng Igarashi, Yasunobu Hashimoto, Koichi Tohoku Univ Grad Sch Informat Sci Aoba Ku 6-6-01 Aramaki Aza Aoba Sendai Miyagi 9808579 Japan Nara Inst Sci & Technol Grad Sch Informat Sci Nara 6300192 Japan Guizhou Univ Coll Elect Engn Guiyang 550003 Peoples R China

ISBN: (纸本)9783642046964

We proposed a parallel level set method with displacement correction (DC) to solve collision problems during tracking a single moving object. The major collision scenarios are that the target cell collides with other cells, air bubbles, or a wall of the water pool where cells swim. These collisions result in detected contour of the target spreading to the other obstacles which induces target missing and tracking failure. To overcome this problem, we add displacement correction to the procedure of boundary detection once the collision occurs. The intensity summation of inside detected contour is utilized to determine whether collision occurs. After the collision is detected, we translate the current level set function according to the displacement information of target cell. To clarify the ability of our proposed method, we try cell (paramecium) tracking by visual feedback controlling to keep target cell at the center of a view field under a microscope. To reduce computational time, we implement our proposed method in a column parallel vision (CPV) system. We experimentally show that the combination of our proposed method and CPV system can detect the boundary of the target cell within about 2 [ms] for each frame and robustly track cell even when the collision occurs.

关键词： boundary tracking parallel image processing level set method displacement correction

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Two-pass hexagonal algorithm with parallel implementation for video coding

Two-pass hexagonal algorithm with parallel implementation fo...

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International Conference on Computer as a Tool (EUROCON 2005)

作者： Wu, YS Megson, G Univ Reading Sch Syst Engn Reading RG6 2AH Berks England

ISBN: (纸本)142440049X

This paper presents a paralleled Two-Pass Hexagonal (TPA) algorithm constituted by Linear Hashtable Motion Estimation Algorithm (LHMEA) and Hexagonal Search (HEXBS) for motion estimation. In the TPA, Motion Vectors (MV) are generated from the first-pass LHMEA and are used as predictors for second-pass HEXBS motion estimation, which only searches a small number of Macroblocks (MBs). We introduced hashtable into video processing and completed parallel implementation. We propose and evaluate parallel implementations of the LHMEA of TPA on clusters of workstations for real time video compression. It discusses how parallel video coding on load balanced multiprocessor systems can help, especially on motion estimation. The effect of load balancing for improved performance is discussed. The performance of the algorithm is evaluated by using standard video sequences and the results are compared to current algorithms.

关键词： parallel image processing video compression parallel computing motion estimation

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Analog VLSI motion projects at Caltech

Analog VLSI motion projects at Caltech

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Conference on Advanced Focal Plane Arrays and Electronic Cameras (AFPAEC 96)

作者： Kramer, J Indiveri, G Koch, C Univ. of Zurich (Switzerland) California Institute of Technology (United States)

ISBN: (纸本)0819423548

We present different compact analog VLSI motion sensors that compute the 1-D velocity of optical stimuli over a large range and are suitable for integration in focal plane arrays. They have been extensively tested and optimized for robust performance under varying light conditions. Since their output signals are only weakly dependent on contrast, they directly extract optical pow data from an image. Focal plane arrays of such sensors ore particularly interesting for application in single-chip systems that perform navigation tasks for moving robots or vehicles, where light weight, low power consumption, and real-time processing are crucial. Several monolithic motion-processing systems based on such velocity sensors have been built and tested. We describe here three chips, designed for the determination of the focus of expansion, the estimation of the time to contact, and the detection of motion discontinuities respectively. The first two systems have been specifically designed for vehicle navigation tasks. The choice of this application domain allows to make a priori assumptions about the optical pow field that simplifies the structure of the systems and improves their overall performance. The motion-discontinuity-detection system can be more generally used to segment images based on the velocities of its different domains with respect to the camera. It is particularly useful for background-foreground segregation in the case of ego-motion of an autonomous system in a static environment. Test results of the three systems are presented and their performance is evaluated.

关键词： motion sensors velocity sensors optical flow analog VLSI photoreceptors machine vision robot vision smart vision chips parallel image processing

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Fast nonlocal filtering applied to electron cryomicroscopy

Fast nonlocal filtering applied to electron cryomicroscopy

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5th IEEE International Symposium on Biomedical Imaging

作者： Darbon, Jerome Cunha, Alexandre Chan, Tony F. Osher, Stanley Jensen, Grant J. Univ Calif Los Angeles Dept Math Los Angeles CA 90024 USA CALTECH Ctr Adv Comp Res Pasadena CA 91125 USA CALTECH Div Biol Pasadena CA 91125 USA

ISBN: (纸本)9781424420025

We present an efficient algorithm for nonlocal image filtering with applications in electron cryomicroscopy. Our denoising algorithm is a rewriting of the recently proposed nonlocal mean filter. It builds on the separable property of neighborhood filtering to offer a fast parallel and vectorized implementation in contemporary shared memory computer architectures while reducing the theoretical computational complexity of the original filter. In practice, our approach is much faster than a serial, non-vectorized implementation and it scales linearly with image size. We demonstrate its efficiency in data sets from Caulobacter crescentus tomograms and a cryoimage containing viruses and provide visual evidences attesting the remarkable quality of the nonlocal means scheme in the context of cryoimaging. With such development we provide biologists with an attractive filtering tool to facilitate their scientific discoveries.

关键词： nonlocal mean filtering image denoising electron cryomicroscopy image vectorization SMID parallel image processing

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Improved Two-Pass Hexagonal algorithm with parallel implementation for video coding

Improved Two-Pass Hexagonal algorithm with parallel implemen...

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Conference on Real-Time image processing 2006

作者： Wu, Yunsong Megson, Graham Univ Reading Sch Syst Engn Reading RG6 6AA Berks England

ISBN: (纸本)0819461032

This paper presents an improved parallel Two-Pass Hexagonal (TPA) algorithm constituted by Linear Hashtable Motion Estimation Algorithm (LHMEA) and Hexagonal Search (HEXBS) for motion estimation. Motion Vectors (MV) are generated from the first-pass LHMEA and used as predictors for second-pass HEXBS motion estimation, which only searches a small number of Macroblocks (MBs). We used bashtable into video processing and completed parallel implementation. The hashtable structure of LHMEA is improved compared to the original TPA and LHMEA. We propose and evaluate parallel implementations of the LHMEA of TPA on clusters of workstations for real time video compression. The implementation contains spatial and temporal approaches. The performance of the algorithm is evaluated by using standard video sequences and the results are compared to current algorithms.

关键词： image processing parallel image processing hashtable two pass hexagonal search

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Biologically inspired compound eye 14

Biologically inspired compound eye

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14th International Conference on Correlation Optics

作者： Borovytsky, Volodymyr Antonenko, Vitalii Natl Tech Univ Ukraine Igor Sikorsky KPI Opt Engn Dept Pr Perem 37 UA-03056 Kiev Ukraine

ISBN: (纸本)9781510635111

The paper describes the design of a biologically inspired compound eye. It contains numerous optical channels like facets in a natural compound eye. Each facet has an optical system, several photodetectors with pre-amplifiers and a microcontroller with a multi-channel analog-to-digital converter. The signals coming from the photodetectors in each channel are amplified, converted into a digital form and processed by a microcontroller. All microcontrollers are attached to a microcontroller network. These microcontrollers can be reprogrammed to perform various image processing operations including spatial filtration, temporal filtration, correlation calculation, neural network simulation and others. It makes possible investigation and performance evaluation of the compound eye when all its facets perform parallel image processing and image analysis. The working prototype of this compound eye has demonstrated ability to measure distribution of speed and direction of optical flow thought its field of view. The possible improvements and possible applications of this design are also discussed.

关键词： compound eye artificial eye bionic eye biologically-inspired vision image sensor facet correlation technique parallel image processing

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A thread concept for automatic task parallelization in image analysis

A thread concept for automatic task parallelization in image...

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SPIE Conference on parallel and Distributed Methods for image processing II

作者： Luckenhaus, M Eckstein, W Munchen Univ Technol Inst Comp Sci Forschungsgrp Bildverstehen D-81667 Munich Germany

ISBN: (纸本)0819429074

parallel processing of image analysis tasks is an essential method to speed up image processing and helps to exploit the full capacity of distributed systems. However, writing parallel code is a difficult and time-consuming process and often leads to an architecture-dependent program that has to be re-implemented when changing the hardware. Therefore it is highly desirable to do the parallelization automatically. For this we have developed a special kind of thread concept for image analysis tasks. Threads derivated from one subtask may share objects and run in the same context but may process different threads of execution and work on different data in parallel. In this paper we describe the basics of our thread concept and show how it can be used as basis of an automatic task parallelization to speed up image processing. We further illustrate the design and implementation of an agent-based system that uses image analysis threads for generating and processing parallel programs by taking into account the available hardware. The tests made with our system prototype show that the thread concept combined with the agent paradigm is suitable to speed up image processing by an automatic parallelization of image analysis tasks.

关键词： automatic parallelization parallel image processing multi-agent system thread concept mapping scheduling modelling

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Real-time efficient parallel thermal and visual face recognition fusion

Real-time efficient parallel thermal and visual face recogni...

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6th IEEE International Conference on Electro/Information Technology (EIT 2006)

作者： Ali, Usman Taj, Jahanzeb Ahmad Hussain, Talib Hussain, Mazhar COMSATS Inst Informat Technol Abbottabad Pakistan

ISBN: (纸本)9780780395930

parallel architecture for fast and efficient visual and thermal face recognition fusion biometric system is presented in this paper. Almost all the decision fusion techniques, in the literature, are computationally expensive. Gabor filter technique is used for recognition of features from input image and the database images. As Gabor filter itself has high computational requirements, so we have proposed a parallel solution, which is fast and efficient. Paper also discusses the performance issues of cluster computing based parallel face recognition along with its limitations and benefits.

关键词： Gabor filter parallel image processing cluster computing decision fusion face recognition

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parallel IMPLEMENTATION OF AN ERROR DIFFUSION HALFTONING ALGORITHM WITH A GENERAL PURPOSE GRAPHICS processing UNIT

PARALLEL IMPLEMENTATION OF AN ERROR DIFFUSION HALFTONING ALG...

引用

IEEE International Conference on image processing

作者： Seong, Becksang Ahn, Jaewoo Sung, Wonyong Seoul Natl Univ Sch Elect Engn Seoul 151 South Korea

ISBN: (纸本)9781424479948

General purpose graphics processing units (GPGPUs) contain many execution units, thus they are very attractive for high speed image processing. However, the error diffusion halftoning algorithm can hardly exploit the benefit of massively parallel processing architecture because this algorithm uses feedback of the output error as well as the results of neighboring pixels. In this study, pixels that can be processed without dependency are found by examining the dependency graph. Also, a parallel processing method requiring less synchronization overhead is developed by considering the characteristics of GPGPUs.

关键词： Halftoning error diffusion general purpose graphics processing unit parallel image processing

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Initial Results on the Effectiveness of Distributed Edge Detection for Large image Data Sets

Initial Results on the Effectiveness of Distributed Edge Det...

引用

SoutheastCon Conference

作者： Renato, Ivanescu Constantin Mihai, Mocanu Univ Craiova Dept Comp & Informat Technol Craiova Romania

ISBN: (纸本)9781665406529

image data is expanding rapidly, along with technology development, so efficient solutions must be considered to achieve high, real-time performance in the case of processing large image datasets. parallel processing is increasingly used as an attractive alternative to improve the performance, when using existing distributed architectures but also for sequential commodity computers. It can provide speedup, efficiency, reliability, incremental growth, and flexibility. We present such an alternative and stress the effectiveness of the methods to accelerate computations on a small cluster of PCs compared to a single CPU. Our paper is focused on applying edge detection on large image data sets, as a fundamental and challenging task in image processing and computer vision. Five different techniques, mainly Sobel, Prewitt, LoG, Canny, and Roberts, are compared in a simple experimental setup that includes the OpenCV library functions for image pixels manipulation. Gaussian blur is used to reduce high-frequency components to manage the noise that edge detection is impacted by. Overall, this work is part of a more extensive investigation of image segmentation methods on large image datasets, but the results presented are relevant and show the effectiveness of our approach.

关键词： parallel image processing edge detection OpenCV MPI

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