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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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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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Equivalence classes of boolean functions

Equivalence classes of boolean functions

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作者： Stankovíc, Radomir S. Stankovíc, Stanislav Astola, Helena Astola, Jaakko T. Department of Computer Science Faculty of Electronics University of Niš Niš Serbia Faculty of Computing and Electrical Engineering Tampere University of Technology Tampere Finland Tampere University OfTechnology Tampere Finland Department of Signal Processing University of Technology Tampere Finland Academy of Finland Centre of Excellence in Signal Finland

ISBN: (纸本)9781608451821

There are 22ν switching functions on n variables. Even for moderate values of n, this is a large number. To handle this complexity, n-variable switching functions are ivided into classes under a set of selected classification rules. The rules are such that, once a representative function of a class is realized, the transformation to any other function in the class corresponds to modifications that are natural for the chosen technology. To be most useful, the classifications should have as few classes as possible, and the set of rules should be simple. In this chapter, we review a few classifications including the classifications based on manipulation with Boolean expressions (NPN-classification), through LP-classification,SD-classification, and classification byWalsh spectra andWalsh decision diagrams.

关键词： Boolean functions

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Gaussian modeling and discrete cosine transform for efficient and automatic palmprint identification

Gaussian modeling and discrete cosine transform for efficien...

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1st International Conference on Machine and Web Intelligence, ICMWI 2010

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 Algeria School of Computing Engineering and Information Sciences Northumbria University Pandon Building Newcastle upon Tyne United Kingdom

ISBN: (纸本)9781424486113

Automatic personal identification using biometric information is playing a more and more important role in applications such as public security, access control, banking, etc. Palmprint identification is a subcategory of biometrics identification, which can efficiently used to identify the people. It is for this reason that palmprint-based identification is becoming increasingly popularity in recent years. In this paper, we present a novel scheme for palmprint identification using the multi-variate Gaussian Probability Density Function (GPDF) and two-dimensional Block based Discrete Cosine Transform (2D-BDCT). In this method, a palmprint is firstly divided into overlapping and equal-sized blocks, and then, applies the discrete cosine transform over each block. By using zigzag scan order (starting at the top-left) each transform block is reordered to produce the observation vector. Subsequently, we use the Gaussian probability density function for modeling the feature vector of each palmprint. Finally, Log-likelihood scores are used for palmprint matching. The proposed scheme is validated for their efficacy on PolyU palmprint database of 100 users. Our experimental results show the effectiveness and reliability of the proposed approach, which brings both high identification accuracy rate. © 2010 IEEE.

关键词： Biometrics

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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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ACS/IEEE International Conference on computer Systems and Applications

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

关键词： Iris recognition Feature extraction Entropy Iris Transforms Vectors Random variables

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Gaussian modeling and Discrete Cosine Transform for efficient and automatic palmprint identification

Gaussian modeling and Discrete Cosine Transform for efficien...

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International Conference on Machine and Web Intelligence (ICMWI)

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 Bab-Ezzouar Algeria School of Computing Engineering and Information Sciences Northumbria University Newcastle-upon-Tyne UK

关键词： Feature extraction Discrete cosine transforms Databases Accuracy Hidden Markov models Probability density function

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Evaluating the Response Time of Large Scale Content Adaptation Systems Using Performance Evaluation Process Algebra

Evaluating the Response Time of Large Scale Content Adaptati...

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IEEE International Conference on Communications (ICC)

作者： J. Ding J. Hillston D. I. Laurenson The University of Edinburgh Edinburgh Edinburgh GB Laboratory of Foundations of Computer Science School of Informatics University of Edinburgh Edinburgh UK Institute of Digital Communications Joint Research Institute of Signal & Image Processing School of Engineering University of Edinburgh Edinburgh UK

With the increasing diversity of content as well as user preferences, and the heterogeneity of devices and network technologies, content adaptation has been widely acknowledged as an effective strategy to deliver services and content to users in a variety of contexts. This paper presents an evaluation of the response time of large scale content adaptation systems being developed under the auspices of the Mobile VCE, using the high-level modelling formalism -performance evaluation process algebra (PEPA). The relevant factors of the system performance, including the operation speed of individual entities, loading and resource conditions of the system, are determined and analysed.

关键词： Delay Large-scale systems Algebra Mobile communication Informatics Context-aware services Performance analysis Velocity measurement Time measurement Communications Society

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A robust face detection method using intrinsic images and an energy minimization technique under the near-IR light spectrum

A robust face detection method using intrinsic images and an...

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2009 International Conference on Image processing, computer Vision, and Pattern Recognition, IPCV 2009

作者： Lahlou, Mouncef Adjouadi, Malek Barreto, Armando Center for Advanced Technology and Education Department of Electrical and Computer Engineering Florida International University Miami FL United States Digital Signal Processing Laboratory Department of Electrical and Computer Engineering Florida International University Miami FL United States

ISBN: (纸本)9781601321190

Detecting faces accurately under natural lighting conditions remains a challenging task for advancing the performance of face recognition systems. Most face detection algorithms are associated with visible spectrum imagery which compromises their efficiency when image acquisition is subject to variable illumination. In this study, we propose a simple yet powerful solution that uses multiple cues to detect and locate faces accurately in near infrared (NIR) imaging systems. Specific objectives include (I) extract optimally the illumination and reflectance components of the original image using an intrinsic images decomposition technique, (2) modify the segmentation process by using an energy minimization procedure in an adaptive fashion, and (3) propose an enhanced face detection process on the basis of pupil localization. The evaluation of our face detector on image sequences of 45 different subjects from the CBSR NIR face dataset demonstrated a highly competitive accuracy with less than 5% error rate.

关键词： Face recognition

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Reflectance measurement system for skin color modeling in chromaticity color space

Reflectance measurement system for skin color modeling in ch...

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2009 16th International Conference on Systems, signals and Image processing, IWSSIP 2009

作者： Kramberger, Iztok University of Maribor Faculty of Electrical Engineering and Computer Science Laboratory for Digital and Information Systems Smetanova ulica 17 SI-2000 Maribor Slovenia

ISBN: (纸本)9781424445301

Experimental skin reflectance measurement setup is presented to acquire skin color signals under different illuminant conditions directly by an image sensor. To obtain stimulus of varying illuminant conditions an adjustable RGB light source is used. Skin color modeling is an important step for efficient skin color image segmentation, which plays an important role when defining regions of interest in image sequence for a successful hand tracking and gesture recognition within spatially defined vision based interaction. To improve detection accuracy of pixel based skin color segmentation a parametric skin color model can be used, which is able to adapt different illuminant conditions. Therefore skin reflectance under different illuminants plays an important role to obtain such a model. Experimental results of hand skin reflectance measurements within chromaticity space are shown. ©2009 IEEE.

关键词： Color

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