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检索条件"任意字段=2017 Conference on Design and Architectures for Signal and Image Processing, DASIP 2017"

共 891 条记录，以下是601-610 订阅

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FPGA implementation of a wideband Gaussian random number generator with low resource utilization

FPGA implementation of a wideband Gaussian random number gen...

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IEEE signal processing and Communications Applications (SIU)

作者： Cansu Şen Soner Yeşil Mühendislik Grup Başkanlığı Aselsan A.Ş. Ankara Türkiye

This work presents a low-complexity hardware implementation of highly accurate wide-band Gaussian noise generator based on the Ziggurat method. Different from the previous works in the literature, the Ziggurat Algorithm is modified such that the computations are done over only three equal regions, yielding important savings in the resource utilization. For the verification of the design, Chi-square Goodness-of-Fit, Anderson Darling, and Kolmogorov-Smirnov tests have been applied together with the bit error rate (BER) measurements on the ZedBoard XC7Z020. Regarding the resource utilization, bandwidth and accuracy requirements, several architectures and their implementation results are presented. Implementation in Xilinx Zynq 7045-3 SoC device resulted in 205 Slices, 14 DSPs and 1-BRAM as for the lowest resource utilization, and 330MHz as for the highest signal bandwidth.

关键词： Field programmable gate arrays Dogs Generators signal to noise ratio Resource management Digital signal processing Hardware

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Compressive information acquisition with hardware impairments and constraints: A case study

Compressive information acquisition with hardware impairment...

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IEEE International conference on Acoustics, Speech and signal processing

作者： S. Gopalakrishnan T. Moy U. Madhow N. Verma University of California Santa Barbara Department of ECE 93106 USA Princeton University Department of EE NJ 08544 USA

ISBN: (纸本)9781509041183

Compressive information acquisition is a natural approach for low-power hardware front ends, since most natural signals are sparse in some basis. Key design questions include the impact of hardware impairments (e.g., nonlinearities) and constraints (e.g., spatially localized computations) on the fidelity of information acquisition. Our goal in this paper is to obtain specific insights into such issues through modeling of a Large Area Electronics (LAE)-based image acquisition system. We show that compressive information acquisition is robust to stochastic nonlinearities, and that appropriately designed spatially localized computations are effective, by evaluating the performance of reconstruction and classification based on the information acquired.

关键词： Compressed sensing stochastic nonlinearities image acquisition low-power front ends hardware impairments information gathering image samples Compressed sensing Computer hardware nonlinearity physical impairment

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design and implementation of blowfish algorithm using reconfigurable platform

Design and implementation of blowfish algorithm using reconf...

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International conference on Recent Innovations in signal processing and Embedded Systems (RISE)

作者： Shraphalya B. Nalawade Dhanashri H. Gawali Department of Electronics and Telecommunication Engineering Savitribai Phule Pune University Pune

ISBN: (纸本)9781509047611;9781509047604

Security is an important issue during communication and data transmission. There are many ways to provide security. One method to ensure security is the use of cryptographic algorithms such as DES, AES, RC5, Blowfish etc. Cryptography is a method used for encoding the data which may be hacked by the unauthorized person. In this paper FPGA based design and implementation of Blowfish algorithm has been proposed. For RTL coding VHDL has been used and Virtex-5XC5VLX50T FPGA device used as a reconfigurable platform for implementation of Blowfish algorithm. The aim of this system is to evaluate performance of Blowfish algorithm on reconfigurable platform in terms of power consumption and throughput. For testing purpose image data and ECG data has been used as plaintext.

关键词： Encryption Field programmable gate arrays Throughput Power demand signal processing algorithms

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Multi-scale spot segmentation with selection of image scales

Multi-scale spot segmentation with selection of image scales

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IEEE International conference on Acoustics, Speech and signal processing

作者： Bertha Mayela Toledo Acosta Antoine Basset Patrick Bouthemy Charles Kervrann Inria Centre Rennes - Bretagne Atlantique France

ISBN: (纸本)9781509041183

Detecting spot-like objects of different sizes in images is needed in many applications. Multiple image scales must then be handled for reliable spot segmentation. We define an original criterion based on the a contrario approach and the LoG scale-space framework to automatically select the meaningful scales. We then design a coarse-to-fine multi-scale spot segmentation scheme involving a locally adaptive thresholding across scales, to come up with the final map of segmented spots. We report experimental results on simulated and real images of different types, and we demonstrate that our method outperforms other existing methods.

关键词： Multi-scale spot detection automatic scale selection a contrario approach object segmentation Object segmentation images Spot Spots Dermal denticles spot fish imagery (Psychotherapy) BALANCES multi-scale segmentation Segmentation image scale simulating

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design of Orthonormal Haar-like Features for Fast Pattern Matching

Design of Orthonormal Haar-like Features for Fast Pattern Ma...

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European signal processing conference

作者： Izumi Ito Karen Egiazarian School of Engineering Tokyo Institute of Technology Tokyo Japan Signal Processing Laboratory Tampere University of Technology Tampere Finland

The goal of pattern matching is to find small parts of an image that are similar to a given template. Matching in transform-domain (such as Haar, Walsh-Hadamard, etc.) is more efficient that matching in the spatial domain. However, it has a limitation: the template size is restricted to be a power of two to apply fast computational algorithms of transforms. In this paper, fast pattern matching method based on orthonormal tree-structured Haar transform (OTSHT) is proposed. It allows to overcome the above-mentioned limitation of the template size. Two types of tree structures are considered in this paper: balanced tree and logarithmic tree. It is demonstrated that the proposed method with the balanced tree structure is computationally more efficient.

关键词： Built-in self-test Pattern matching Transforms Strips Binary trees signal processing

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Directional graph weight prediction for image compression

Directional graph weight prediction for image compression

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IEEE International conference on Acoustics, Speech and signal processing

作者： Francesco Verdoja Marco Grangetto Universita degli Studi di Torino Dept. of Computer Science Italy

ISBN: (纸本)9781509041183

Graph-based models have recently attracted attention for their potential to enhance transform coding image compression thanks to their capability to efficiently represent discontinuities. Graph transform gets closer to the optimal KLT by using weights that represent inter-pixel correlations but the extra cost to provide such weights can overwhelm the gain, especially in the case of natural images rich of details. In this paper we provide a novel idea to make graph transform adaptive to the actual image content, avoiding the need to encode the graph weights as side information. We show that an approach similar to spatial prediction can be used to effectively predict graph weights in place of pixels;in particular, we propose the design of directional graph weight prediction modes and show the resulting coding gain. The proposed approach can be used jointly with other graph based intra prediction methods to further enhance compression. Our comparative experimental analysis, carried out with a fully fledged still image coding prototype, shows that we are able to achieve significant coding gains.

关键词： image compression graph transform directional prediction image compression Data compression coding gain Line graph

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Transform Learning Algorithm Based on the Probability of Representation of signals

Transform Learning Algorithm Based on the Probability of Rep...

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European signal processing conference

作者： Gayatri Parthasarathy G. Abhilash Department of Electronics and Communication Engineering National Institute of Technology Calicut Kerala India

Compressed sensing is a signal acquisition scheme that measures signals at sub-Nyquist rate amenable to sparse recovery, with high probability, from a reduced set of measurements. One of the main requirements of compressive sensing is the sparsity of the class of signals of interest in some basis. A method to construct a sparsifying basis for a class of signals using information theoretic measures is proposed in this paper. The algorithm constructs the sparsifying basis from a known non-sparsifying basis by concentrating the probability distribution of the basis in the representation of a class of signals. Simulation studies using speech and image signals confirm that the basis constructed using the proposed method results in an improved sparsity of the signals with thresholded coefficients but without degrading the signal quality.

关键词： Transforms Entropy signal processing algorithms Training Optimization Dictionaries Algorithm design and analysis

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A Highly Efficient and Comprehensive image processing Library for C++-based High-Level Synthesis

A Highly Efficient and Comprehensive Image Processing Librar...

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FSP 2017;Fourth International Workshop on FPGAs for Software Programmers

作者： M. Akif Oezkan Oliver Reiche Frank Hannig Juergen Teich Friedrich-Alexander University Erlangen-Nurnberg (FAU)

ISBN: (纸本)9783800744435

Field Programmable Gate Arrays (FPGAs) are proved to be among the most suitable architectures for image processing applications. However, accelerating algorithms using FPGAs is a time-consuming task and needs expertise. Whereas the recent advancements in High-Level Synthesis (HLS) promise to solve this problem, today's HLS tools require apt hardware descriptions of algorithms to be able to provide favorable implementations. A solution is developing highly parameterizable and optimized HLS libraries for the fundamental image processing components. Another solution is providing a higher level of abstraction in the form of a Domain-Specific Language (DSL) and a corresponding efficient back end for hardware design. In this paper, we provide a highly efficient and parameterizable C++ library for image processing applications, which would be the cornerstone for both approaches. In our library, nodes of a stream-based data flow graph can be described as C++ objects for specified functions, and the whole application can be efficiently parallelized just by defining a global constant as the parallelization factor. Moreover, the key hardware design elements, i. e., line buffers and sliding windows with different border handling patterns, can be utilized individually to ease the design of more complicated applications.

关键词： level of abstraction computer hardware design image processing hue lightness saturation Libraries high level synthesis Field programmable gate arrays data flow graphs Cornerstones Abstraction algorithms

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Multiple-input multiple-output (MIMO) MRI: An efficient pulse design algorithm to combine parallel excitation and parallel imaging

Multiple-input multiple-output (MIMO) MRI: An efficient puls...

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IEEE International conference on Acoustics, Speech and signal processing

作者： Xianglun Mao David J. Love Joseph V. Rispoli Thomas M. Talavage School of Electrical & Computer Engineering Purdue University IN 47907 USA Weldon School of Biomedical Engineering Purdue University IN 47907 USA

ISBN: (纸本)9781509041183

Magnetic resonance imaging (MRI) plays a critical role in medicine today. Over the last few years, there has been an interest in techniques that use multiple coils on one side of the imaging system such as parallel excitation or parallel imaging to improve performance in high-field MRI. In this paper, we explore the use of multiple coils at both the transmit and receive sides for enhanced imaging. We term this a multiple-input multiple-output (MIMO) MRI system. We use tools from the well-developed MIMO communication models and propose a novel radio-frequency (RF) pulse design method for multiple coils. We show that our MIMO MRI techniques can provide an improved signal-to-noise ratio (SNR) in the reconstructed image.

关键词： MRI MIMO parallel excitation parallel imaging RF pulse design parallel excitation multiple input multiple output systems Magnetic Resonance Imaging C7orf49 gene RF pulse multicoil signal to noise ratios design Algorithm

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Software design of DC insulator surface pollution analysis device

Software design of DC insulator surface pollution analysis d...

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2017 EPTC Power Transmission and Transformation Technology conference

作者： Yang Zhang Ran Jia Hui Liu Chao Zhou Rong Liu State Grid Shan Dong Electric Power Research Institute Jinan China

ISBN: (纸本)9781510872738

Surface pollution monitoring and evaluation of DC line insulators is an important ways to improve the pertinence and efficiency of anti-pollution flashover measures. The design and development of software for surface pollution analysis of DC insulators based on the synergetic evaluation of surface leakage current and visible light images are presented. Through the collection, processing and optimization comparison of the visible light image signal and the DC leakage current signal of the DC insulator surface, the pollution detection and pollution flashover warning of the insulators on the DC line are realized.

关键词： DC INSULATOR POLLUTION ANALYSIS SOFTWARE LEAKAGE CURRENT image RECOGNITION computer software insulators image recognition leakage currents direct current surface leakage current pollution detection and control Surfaces

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