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作者： Meraoumia, Abdallah Chitroub, Salim Bouridane, Ahmed Laboratoire de Génie Électrique Faculté de Science et de la Technologie et des Sciences de la Matière Université Kasdi Merbah de Ouargla Algeria Signal and Image Processing Laboratory Electronics and Computer Science Faculty Telecommunication Department Electronics and Computer Science Faculty University of Science and Technology of Houari Boumedienne Algiers Algeria School of Computing Engineering and Information Sciences Northumbria University Pandon Building Newcastle upon Tyne United Kingdom

Biometric systems based on a single source of information suffer from limitations such as the lack of uniqueness, non-universality of the chosen biometric trait, noisy data and spoof attacks. Multimodal biometrics are relatively new systems that overcome those problems. These systems fuse information from multiple sources in order to achieve the better person recognition performance. In this paper, the 2D and 3D information of palmprint are integrated in order to construct an efficient multimodal biometric system based on fusion at matching score level and at feature extraction level. The observation vectors are created independently either from the original data of the two modalities (2D and 3D palmprint) or from their rotation invariant variance measures applied on textures. On each modality (or its corresponding invariant texture), we have applied the Principal Component Analysis (PCA) for reducing dimension of the feature vector. We have also used the multi-scale wavelet decomposition for each modality and the results of decomposition are combined and compressed using PCA for selecting the feature vectors. Subsequently, we have used the Hidden Markov Model (HMM) for modeling the feature vectors. Finally, Log-likelihood scores are used for palmprint evaluation. We note that the selected principal components of two modalities are fused at feature level and at matching score level. The proposed scheme is tested and evaluated using PolyU 2D and 3D palmprint database of 250 persons. Our experimental results show the effectiveness and reliability of the proposed system, which brings high identification accuracy rate. © 2013 - IOS Press and the author(s). All rights reserved.

关键词： Hidden Markov models

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Depth data filtering for real-time head pose estimation with Kinect

Depth data filtering for real-time head pose estimation with...

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Congress on image and signal processing, CISP

作者： Ti-zhou Qiao Shu-ling Dai School of Automation Science and Electronic Engineering Beijing University of Aeronautics and Astronautics China

In order to analyze the head motion of pilots in real time and improve tracking performance, we propose a method based on the random regression forest framework to address head pose estimation from depth data captured by Kinect sensors. We present the novel Trinary Annulus Filter and implement Bilateral Filtering using CUDA to process depth data of Kinect, with the purpose of image quality improvement and minimized performance impact. We have evaluated our system on a public database, and it is proved to be more effective after depth data processing and capable of handling large and rapid head rotations, temporary and partial occlusions in performance evaluation. After head pose data are filtered by presented multiple pose estimation method, they are successfully used in flight simulation to drive the rotation of viewpoint.

关键词： Head Estimation Training Filtering Real-time systems Accuracy Sensors

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Featured circular profile for vessel thresholding

Featured circular profile for vessel thresholding

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Congress on image and signal processing, CISP

作者： Na Lu Hongyu Miao State Key Laboratory for Manufacturing Systems Engineering Xi'an Jiaotong University Xi'an Shaanxi China Department of Biostatistics and Computational Biology University of Rochester NY USA

ISBN: (纸本)9781479927654

To analyze the characteristics of the blood vessels quantitatively is of great importance to the diagnosis of different diseases, e.g., stenosis, diabetic retinopathy, tumor and so on. However, the occurrence of imaging noise or illumination variation may include difficulty for image analysis, especially for accurate quantitative analysis. Therefore, more efficient algorithms for vessel image thresholding, segmentation or extraction have been studied. Nevertheless, these methods may still fail entirely in case of images with large noise or structural noise (such as spots that obscure and/or are brighter than vessels). To improve the algorithm performance on these issues, we propose a novel thresholding algorithm for vascular images by probing the polarity in the circular profiles (PCP) of image pixels. This can robustly distinguish tube-like objects from both cloud-like contaminations and structural noise. Extensive simulation studies based on multiple evaluation criteria suggest that the PCP algorithm typically has a superior performance over other representative approaches. Finally, we also demonstrate the satisfactory performance of the PCP method on real image data.

关键词： Noise Contamination Probes Algorithm design and analysis Shape signal processing algorithms Graphical models

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performance evaluation and comparison of modified denoising method and the local adaptive wavelet image denoising method

Performance evaluation and comparison of modified denoising ...

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International Conference on Intelligent systems and signal processing (ISSP)

作者： Jignasa M. Parmar S. A. Patil Department of Electronics and Telecommunication R. C. Patel Institute of Technology Dist-Dhule MS India

ISBN: (纸本)9781479903160

Removal of noise is an important step in the image restoration process, but denoising of image remains a challenging problem in recent research associate with image processing. Denoising is used to remove the noise from corrupted image, while retaining the edges and other detailed features as much as possible. This noise gets introduced during acquisition, transmission & reception and storage & retrieval processes. In this paper, to find out denoised image the modified denoising method and the local adaptive wavelet image denoising method can be used. The noisy image is denoised by modified denoising method which is based on wavelet domain and spatial domain and the local adaptive wavelet image denoising method which is based on wavelet domain. In this paper, we have evaluated and compared performances of modified denoising method and the local adaptive wavelet image denoising method. These methods are compared with other based on PSNR (Peak signal to noise ratio) between original image and noisy image and PSNR between original image and denoised image. simulation and experiment results for an image demonstrate that RMSE of the local adaptive wavelet image denoising method is least as compare to modified denoising method and the PSNR of the local adaptive wavelet image denoising method is high than other method. Therefore, the image after denoising has a better visual effect. In this paper, these two methods are implemented by using MATLAB for denoising of image.

关键词： Wiener filters Wavelet transforms image denoising Wavelet domain PSNR

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GPU-based infrared sensor model capable of operating in real time

GPU-based infrared sensor model capable of operating in real...

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IEEE signal processing and Communications Applications (SIU)

作者： Mehmet Serkan Tokay Ziya Gürkan Fi̇gen TÜBİTAK BİLGEM İLTAREN Ankara Turkey

This work describes a Graphic processing Unit (GPU) based Infrared (IR) Sensor Model Software capable of operating in real time which has been recently developed by us. This module, which is based on physical models, is capable of simulating the images registered by an infrared imager. The software is also capable of accounting for the image degradations (blur and noise) by applying these effects on synthetic images generated by an IR Scene Generator Software at high frame rates. In this module, in order to enable processing of large format images at high frame rates, the parallel computations are carried out on the GPU. In this work, we achieved a performance increase when compared to the results of an earlier and similar work presented by us. In order to decrease the execution time, some routines (especially those pertaining to between GPU with CPU data transfer) have been improved. In order to determine the runtime performance of the module, the module has been run in a closed loop where IR Scene Generator and Target Detection / Tracking Modules also exist and maximum achievable frame rates corresponding to different image sizes have been recorded. We believe this study will support the efforts for developing closedloop simulation systems employing the method of signal injection.

关键词： Graphics processing units Atmospheric modeling Noise Imaging Real-time systems Central processing Unit

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GPP vs DSP: A performance/Energy Characterization and evaluation of Video Decoding

GPP vs DSP: A Performance/Energy Characterization and Evalua...

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International Symposium on modeling, Analysis and simulation of Computer and Telecommunication systems (MASCOTS)

作者： Yahia Benmoussa Jalil Boukhobza Eric Senn Djamel Benazzouz Univ. M'hamed Bougara LMSS Boumerdes Algeria Univ. Bretagne Sud Lab-STICC Lorient France

Mobile devices such as smart-phones and tablets are increasingly becoming the most important channel for delivering end-user Internet traffic especially multimedia content. One of the most popular use of these terminals is video streaming. In this type of application, video decoding is considered as the most compute and energy intensive part. Some specific processing units, such as dedicated Digital signal Processors (DSPs), are added to those devices in order to optimize the performance and energy consumption. In this context, the objective of this paper is to give a comprehensive and comparative study of the performance and energy consumption of video decoding application on embedded heterogeneous platforms containing a GPP and a DSP. To achieve this goal, a performance and energy characterization methodology for H.264/AVC video decoding is proposed. This methodology considers a large set of video coding parameters and operating clock frequencies to reflect different execution scenarios ranging from low-quality video decoding on low-end mobile phones to high-quality video decoding on tablets. The obtained results revealed that the best performance-energy trade-off highly depends on the required video bit-rate and resolution. For instance, the GPP can be the best choice in many cases due to a significant overhead in DSP decoding which may represent 30% of the total decoding energy in some cases. Some explanations about the obtained performance and overheads are given. Finally, guidelines on which processing element to choose according to video properties are also proposed.

关键词： Decoding Digital signal processing Streaming media Clocks Power demand Energy consumption Hardware

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On-demand thread-level fault detection in a concurrent programming environment

On-demand thread-level fault detection in a concurrent progr...

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International Conference on Embedded Computer systems: Architectures, modeling and simulation (IC-SAMOS)

作者： Jian Fu Qiang Yang Raphael Poss Chris R. Jesshope Chunyuan Zhang Universiteit van Amsterdam Amsterdam Noord-Holland NL Informatics Institute University of Amsterdam Amsterdam Netherlands School of Computer National University of Defence Technology Changsha China

ISBN: (纸本)9781479901043

The vulnerability of multi-core processors is increasing due to tighter design margins and greater susceptibility to interference. Moreover, concurrent programming environments are the norm in the exploitation of multi-core systems. In this paper, we present an on-demand thread-level fault detection mechanism for multi-cores. The main contribution is on-demand redundancy, which allows users to set the redundancy scope in the concurrent code. To achieve this we introduce intelligent redundant thread creation and synchronization, which manages concurrency and synchronization between the redundant threads via the master. This framework was implemented in an emulation of a multi-threaded, many-core processor with single, in-order issue cores. It was evaluated by a range of programs in image and signal processing, and encryption. The performance overhead of redundancy is less than 11% for single core execution and is always less than 100% for all scenarios. This efficiency derives from the platform's hardware concurrency management and latency tolerance.

关键词： Redundancy Concurrent computing Message systems Synchronization Instruction sets Programming

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A new method for image de-noising on the basis of Chen-Mobius transform

A new method for image de-noising on the basis of Chen-Mobiu...

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IEEE International Workshop on Imaging systems and Techniques (IST)

作者： Shun-da Lin Department of Physics & Information Engineering Quanzhou Normal University Quanzhou P. R. China

ISBN: (纸本)9781467357890

The purpose of this paper is to study a new method of de-noising images corrupted with additive white Gaussian noise. Based on the Chen-Mobius transform, the idea of modulation and demodulation in Chen-Mobius communication system is applied in the image de-noising. The evaluation results of the Chen-Mobius transform of some often-used waveforms are applied in the anti-noise of image. For image de-noising, the data is modulated on a modulation wave for some period and recorded by a certain means, then the data can be carried everywhere. To make such a processing, the Chen-Mobius inverse transformed functions act as the “modulation” waveforms and the receiving end is coherently “demodulated” by the often-used digital waveforms. simulation results are discussed in some detail. It shows that the new application has excellent performances that the digital image signals can be restored from intense Gaussian noise. Here, to prove the performance of the proposed method, the results are compared with other existent methods or algorithms such as hard and soft threshold based on wavelet. The simulation results on several testing images indicate that the proposed method outperforms the other methods in peak signal to noise ratio and keeps better visual in edges information reservation as well. The results also suggest that Chen-Mobius transform can achieve a better performance than the wavelet transform in image de-noising.

关键词： Communication systems Noise image denoising Demodulation Wavelet transforms

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A Congestion Eliminating Control Method for Large-scale Urban Traffic Networks *

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IFAC Proceedings Volumes 2013年第13期46卷 496-501页

作者： Zhao Zhou Shu Lin Dewei Li Yugeng Xi Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China

This paper investigates an efficiency of signal control methodology, which mainly focuses on dealing with the traffic congestion problem in those key congested links and is applicable to be implemented in a hierarchical control structure in large-scale heterogeneous urban traffic networks. In this methodology, an algorithm for finding the most congested path is presented firstly, and the urban traffic flow is modeled by using a simplified macroscopic modeling framework. Then the problem of network-wide signal control is formulated as a linear programming problem that aims at minimizing the number of vehicles(or densities) in congested links so as to improve the mobility of the network and mitigate the traffic congestion. For the application of this method in real time, the multi-variables optimization problem including constraints is embedded in a model-based dynamic control procedure. Finally, different traffic demand scenarios are designed and four evaluation criteria are applied to measure the performance of the proposed method in a hypothetical road network. Compared with the fixed-time control strategy, the simulation results show that it is an effective and feasible way to regulate the traffic flow and mitigate the congestion in large-scale urban networks.

关键词： Urban traffic networks large-scale systems congested path model-based control hierarchical structure

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Architecture Exploration Based on GA-PSO Optimization, ANN modeling, and Static Scheduling

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VLSI DESIGN 2013年第12013期2013卷 624369-624369页

作者： Elhossini, Ahmed Areibi, Shawki Dony, Robert Al Azhar Univ Cairo 11751 Egypt Univ Guelph Sch Engn Guelph ON N1G 2W1 Canada

Embedded systems are widely used today in different digital signal processing (DSP) applications that usually require high computation power and tight constraints. The design space to be explored depends on the application domain and the target platform. A tool that helps explore different architectures is required to design such an efficient system. This paper proposes an architecture exploration framework forDSP applications based on Particle SwarmOptimization (PSO) and genetic algorithms (GA) techniques that can handle multiobjective optimization problems with several hybrid forms. A novel approach for performance evaluation of embedded systems is also presented. Several cycle-accurate simulations are performed for commercial embedded processors. These simulation results are used to build an artificial neural network (ANN) model that can predict performance/ power of newly generated architectures with an accuracy of 90% compared to cycle-accurate simulations with a very significant time saving. Thesemodels are combined with an analytical model and static scheduler to further increase the accuracy of the estimation process. The functionality of the framework is verified based on benchmarks provided by our industrial partnerONSemiconductor to illustrate the ability of the framework to investigate the design space.

关键词： Particle swarm optimization Exploration performance evaluation ARCHITECTURE Building construction Embedded systems Frameworks BENCHMARKS

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