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IEEE International Conference on Communications (ICC)

作者： Abdallah Meraoumia Salim Chitroub Ahmed Bouridane Signal and Image Processing Laboratory Electronics and Computer Science Faculty University of Sciences and Technology Houari Boumediene Algiers Algeria Department of Computer Science King Saud University Riyadh Saudi Arabia School of Computing Engineering and Information Sciences Northumbria University Newcastle-upon-Tyne UK

ISBN: (纸本)9781457720529

Biometrics is an effective technology for personnel identity recognition, but uni-modal biometric systems which use a single trait for recognition will suffer from problems like noisy sensor data, non-universality, lack of distinctiveness of the biometric trait, and spoof attacks. These problems can be tackled by using multi-biometrics in the system. Hand-based person recognition provides a reliable, low-cost and user-friendly viable solution for a range of access control applications. As one of the most popular biometric traits, fingerprints (FP) are widely used in personal recognition. However, a novel hand-based biometric feature, Finger-Knuckle-Print (FKP), has attracted an increasing amount of attention. In this paper, FP and FKP are integrated in order to construct an efficient multi-biometric recognition system based on matching score level and image level fusion. In this study we use the minimum average correlation energy (MACE) and Unconstrained MACE (UMACE) filters in conjunction with two correlation plane performance measures, max peak value and peak-to-sidelobe ratio, to determine the effectiveness of this method. The experimental results showed that the designed system achieves an excellent recognition rate on the Hong Kong polytechnic university (PolyU) FKP and high resolution fingerprint database.

关键词： Correlation Databases Training Discrete wavelet transforms Biomedical imaging Biometrics (access control) Fingers

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Geese PSO optimization in geometric constraint solving

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information Technology Journal 2012年第4期11卷 504-507页

作者： Cao, Chun-Hong Wang, Li-Min Han, Chun-Yan Zhao, Da-Zhe Zhang, Bin College of Information Science and Engineering Northeastern University Shenyang 110819 China College of Computer Science and Technology Jilin University Changchun Jilin 130012 China State Key Lab. for Novel Software Technology Nanjing University China Key Laboratory of Medical Image Computing Ministry of Education Northeastern University Shenyang Liaoning 110819 China

Geometric constraint problem is equivalent to the problem of solving a set of nonlinear equations substantially. The constraint problem can be transformed to an optimization n problem. We can solve the problem with GeesePSO optimization. In this paper, an improved algorithm is proposed using the characteristics of the flight of geese for reference. The improved algorithm has superiority over PSO;for one thing, it keeps the population various by ordering all the particles and making each particle fly following its anterior particle;for another thing, it strengthens cooperation and competition between particles by making each particle share more useful information of the other particles. The experiment shows that it can improve the geometric constraint solving efficiency and possess better convergence property than the compared algorithms. © 2012 Asian Network for Scientific information.

关键词： Nonlinear equations

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Improving palmprint identification by combining multiple classifiers and using gabor filter

Improving palmprint identification by combining multiple cla...

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IEEE International Conference on Electronics, Circuits and Systems (ICECS)

作者： Abdallah Meraoumia Salim Chitroub Ahmed Bouridane Laboratoire de Génie Électrique. Faculté des Sciences et de la Technologie et des Sciences de la Matière Université Kasdi Merbah Ouargla Ouargla Algeria Signal and Image Processing Laboratory Electronics and Computer Science Faculty Algiers Algeria School of Computing Engineering and Information Sciences Northumbria University Newcastle upon Tyne UK Department of Computer Science King Saud University Riyadh Saudi Arabia

Biometrics technology has been attracting extensive attention from researchers of personal authentication due to the ever growing demand on access control, public security, forensics and e-banking. Diverse biometric systems have been now widely used in various applications. The palmprint is most popular modality that has the largest shares in the biometrics market. In this paper, an efficient online personal identification system based on palmprint is proposed. Firstly, the palmprint is filtered by the Gabor filter. The real and imaginary responses of the filtering are used to create three different feature vectors. Subsequently, the Hidden Markov Model (HMM), the Gaussian Mixture Model (GMM) and the Radial Basis Function (RBF) are used for modeling and so for classifying the feature vectors. The results of the three classifiers are combined using matching score level fusion strategy. The proposed system is tested and evaluated using PolyU 2D and 3D palmprint database of 250 persons. The obtained experimental results show that the system yields the best performance for identifying palmprint and it is able to provide the highest degree of biometrics-based system security.

关键词： Hidden Markov models Vectors Feature extraction Databases Computational modeling Authentication

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2D and 3D palmprint information and hidden Markov model for improved identification performance

2D and 3D palmprint information and hidden Markov model for ...

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2011 11th International Conference on Intelligent Systems Design and Applications, ISDA'11

作者： Meraoumia, Abdallah Chitroub, Salim Bouridane, Ahmed Signal and Image Processing Laboratory Electronics and Computer Science Faculty USTHB P.O. box 32 El Alia Bab Ezzouar 16111 Algiers Algeria School of Computing Engineering and Information Sciences Northumbria University Pandon Building Newcastle upon Tyne United Kingdom Department of Computer Science King Saudi University P.O. Box 2454 Riyadh 11451 Saudi Arabia

ISBN: (纸本)9781457716751

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. Multibiometrics are relatively new systems that overcome those problems. These systems fuse information from multiple biometric sources in order to achieve better identification performance. In this paper, 2D and 3D palmprint are integrated in order to construct an efficient multibiometric identification system based on matching score level fusion. For that, the texture information is characterized by the rotation invariant VARiance measures (VAR) and compressed using the Principal Components Analysis (PCA). Subsequently, we use the Hidden Markov Model (HMM) for modeling the feature vector of each palmprint. Finally, Log-likelihood scores are used for palmprint evaluation. The proposed scheme is tested and evaluated using PolyU 2D-3D palmprint database of 250 users. Our experimental results show the effectiveness and reliability of the proposed system, which brings high identification accuracy rate. © 2011 IEEE.

关键词： Principal component analysis

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复合事件相似性检测技术

复合事件相似性检测技术

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第29届中国数据库学术会议

作者： Wang Ning 王宁 Gu Yu 谷峪 Li Fangfang 李芳芳 Yu Ge 于戈 Institute of Computer Software and Theory of Information Science and Engineering Institute Northeas 东北大学信息科学与工程学院软件与理论研究所沈阳 110819 Key Laboratory of Medical Image Computing(Northeastern University) Ministry of Education Shenyang 医学影像计算教育部重点实验室(东北大学) 沈阳 110819

复杂事件处理一般都是从大量的简单事件进行查找，整理出有价值的复合事件，在事件的查找过程中，强调的是事件的精确性匹配。本文提出了复合事件相似性查询，并且针对其定义，给出了两种剪枝策略。根据复合事件的特点，减少数据处理数... 详细信息

复杂事件处理一般都是从大量的简单事件进行查找，整理出有价值的复合事件，在事件的查找过程中，强调的是事件的精确性匹配。本文提出了复合事件相似性查询，并且针对其定义，给出了两种剪枝策略。根据复合事件的特点，减少数据处理数量，降低I/O代价。最后，利用实验对提出的两种剪枝策略进行对比分析。

关键词：信息处理复杂事件相似性检测射频识别技术

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2D and 3D palmprint information and Hidden Markov Model for improved identification performance

2D and 3D palmprint information and Hidden Markov Model for ...

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International Conference on Intelligent Systems Design and Applications (ISDA)

作者： Abdallah Meraoumia Salim Chitroub Ahmed Bouridane Signal and Image Processing Laboratory Electronics and Computer Science Faculty USTHB Algiers Algeria Department of Computer Science King Saudi University Riyadh Saudi Arabia School of Computing Engineering and Information Sciences Northumbria University Newcastle-upon-Tyne UK

关键词： Three dimensional displays Vectors Hidden Markov models Feature extraction Principal component analysis Databases Reactive power

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Fusion of multispectral palmprint images for automatic person identification

Fusion of multispectral palmprint images for automatic perso...

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Electronics, Communications and Photonics Conference (SIECPC), Saudi International

作者： Abdallah Meraoumia Salim Chitroub Ahmed Bouridane Signal and Image Processing Laboratory Electronics and Computer Science Faculty Telecommunication Department University of Science and Technology of Houari Boumedienne Algiers Algeria School of Computing Engineering and Information Sciences Northumbria University Newcastle-upon-Tyne UK

Reliability and accuracy in personal identification system is a dominant concern to the security world. Biometric has gained much attention in this subject recently. Many types of personal identification systems have been developed, and palmprint identification is one of the emerging technologies. This paper presents a novel biometric technique to automatic personal identification system using multispectral palmprint technology. In this method, each of spectrum images are aligned and then used to extract palmprint features using 1D log-Gabor filter. These features are then examined for their individual and combined performances. Finally, the hamming distance is used for matching of palmprint features. The experimental results showed that the proposed method achieve an excellent identification rate and provide more security.

关键词： Feature extraction Databases image fusion Discrete wavelet transforms Security Accuracy Hamming distance

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Flexible-ICA algorithm for a reliable Iris recognition

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2011年 6990 LNCS卷 188-208页

作者： Bouraoui, Imen Chitroub, Salim Bouridane, Ahmed Signal and Image Processing Laboratory Electronics and Computer Science Faculty USTHB El - Alia Bab - Ezzouar P.O. Box 32 Algiers 16111 Algeria School of Computing Engineering and Information Sciences Northumbria University Pandon Building Newcastle upon Tyne United Kingdom Department of Computer Science King Saud University P.O. Box 2454 Riyadh 11451 Saudi Arabia

ISBN: (纸本)9783642237393

In many large scale biometric-based recognition problems, knowledge of the limiting capabilities of underlying recognition systems is constrained by a variety of factors including a choice of a source encoding technique, quality, complexity and variability of collected data. In this paper, we propose a novel iris recognition system based-on Independent Component Analysis (ICA) encoding technique, which captures both the second and higher-order statistics and projects the input data onto the basis vectors that are as statistically independent as possible. We apply Flexible-ICA algorithm in the framework of the natural gradient to extract efficient feature vectors by minimizing the mutual information of the output data. The experimental results carried on two different subsets of CASIA V3 iris database show that ICA reduces the processing time and the feature vector length. In addition, ICA has shown an encouraging performance which is comparable to the best iris recognition algorithms found in the literature. © 2011 Springer-Verlag Berlin Heidelberg.

关键词： Biometrics

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2010 IEEE 5th International Conference on Bio-Inspired computing: Theories and Applications, BIC-TA 2010

作者： Zhang, Zhujin Wang, Shuo Zhang, Xingyi Zhang, Zheng Department of Control Science and Engineering Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China School of Computer and Information Science University of South Australia Adelaide SA 5095 Australia Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei 230039 China

ISBN: (纸本)9781424464388

Randí et al. proposed a significant graphical representation for DNA sequences, which is very compact and avoids loss of information. In this paper, we build a fast algorithm for this graphical representation with time complexity O(n2), and find another important advantage in the representation: no degeneracy. Moreover, we propose a new method to do similarity analysis of DNA sequences based on the representation. The approach adopts four elements of covariance matrix as a descriptor, and is illustrated on the first exon of beta-globin genes from 11 different species. © 2010 IEEE.

关键词： DNA sequences

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Performance evaluation of independent component analysis in an iris recognition system

Performance evaluation of independent component analysis in ...

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2010 ACS/IEEE International Conference on computer Systems and Applications, AICCSA 2010

作者： Bouraoui, Imen Chitroub, Salim Bouridane, Ahmed Signal and Image Processing Laboratory Electronics and Computer Science Faculty USTHB Algiers Algeria School of Computing Engineering and Information Sciences Northumbria University Pandon Building Newcastle Upon Tyne United Kingdom

ISBN: (纸本)9781424477159

The overall performance of any iris recognition system relies on the performance of its components, which are preprocessing, feature extraction and matching. Feature extraction is the important step of such recognition system, but it is strongly dependent on the pre-processing step that is consisting of localising and normalising the iris. In this paper, Independent Component Analysis (ICA), which is a recently developed statistical method for data analysis, is applied for extracting the features for iris region of interest that are statistically independent. Based on some mathematical criteria, the performance of ICA is evaluated by using two different subsets of CASIA-V3 iris image database. The obtained results are convincing and some future improved research works are subsequently envisaged.

关键词： Feature extraction

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