Nombre total de résultats : 513
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Contribution à l’amélioration des performances du codage turbo dans les systèmes de transmission numériques

Brahim OUDJANI (2018)
Thèse de doctorat

Pour bénéficier des propriétés des codes LDPC (Low-Density-Parity-Check) et Turbo Convolutional Codes (TCC), nous proposons un codage concaténé de type Gallager/Convolutionnel codé de la manière turbo. Le code modifié crée un équilibre entre les avantages et les inconvénients de LDPC et TCC en termes de complexité globale et de latence. Cela se fera à travers deux décodeurs SISO différents; LDPC et code convolutif récursif systématique (RSC) du même taux de code R= 1/2 sans entrelaceur. Étant donné que les deux décodeurs SISO sont de natures différentes, ils échangent des informations extrinsèques qui seront facilement adaptées l’une à l’autre. L'étude de la complexité de calcul et des performances de décodage sur un canal AWGN indique qu'une telle approche conduit à d'excellentes performances en raison de plusieurs facteurs. L'approche proposée réalise un compromis entre les régions de convergence et de plancher d'erreur. Il réduit la complexité de décodage par rapport au TCC et au 3D-TCC. Il fournit un meilleur gain de codage sur LDPC et PCGC (Parallel Concatenated Gallager Codes). Ces caractéristiques assureront un rapport coût-performance optimal. Comme ils peuvent être un meilleur choix pour les systèmes de communication d'aujourd'hui. Voir les détails

Mots clés : Complexité de calcul; Code convolutif; Information extrinsèque; LDPC; Concaténation parallèle; Turbo code.

Performance of some Variational ImplicitDeformable Models on Segmenting OpticalMicroscopy Images

Y. Boutiche, N. Cheteh, N. Ramou (2018)
Article de conférence

Industrial micrographs are used to evaluate a steelsor alloys. This assessment consists of visualizing and describingthe basic element (at the nanoscale) constituting the material.The information provided by the micrographic images needto be highlighted by image processing methods. In this paperthe performance of some region-based variational models arepresented. Such study allows to choose best models that give themore accuracy segmentation in less processing time.Voir les détails

Mots clés : Material microstructures, Microscopy images, segmentation, deformable models, region-based active contours

Video Processing Software-based Pipeline Endoscopic Inspection

Nadia MHAMDA, Nafaa Nacereddine, Aissa Boulmerka (2018)
Article de conférence

Currently, all the codes and the standards of the fluids transport industries require rigorous pipeline inspection, in order to detect all defects and anomalies and avoid leaks and failures. For this reason, a team within the division of Signal Processing and Imagery had as mission to develop an endoscope which can replace the operator inspection inside the pipeline and improve its quality and diagnostic. This endoscope named 'Pipe Explorer' is controlled by FPGA microcontrollers, and is equipped with a camera. While moving inside the pipe, the camera records a video on the memory card. In this way and in order to offer a practical tool to the operator, we have developed graphical software based on processing techniques of the stored video consisting in video preprocessing and segmentation. At the end of this processing, we obtain a video result on which appears the analysis and the interpretation of the original video to give an internal pipe quality diagnosis. The results shows all the defective areas such as corrosion which are stained with {green, blue, red} color according to its degree of severity and the risk of harmfulness on the inspected pipeline.Voir les détails

Mots clés : Pipeline inspection, endoscopy, video processing, video segmentation, corrosion.


A.REDDAF, F. Djerfaf, K.FERROUDJI, M. Boudjerda, K. Hamdi Chérif, I. BOUCHACHI (2018)
Article de conférence

In this study, an extraction procedure using a ground coplanar wave guide GCPWG structure [1] is proposed to obtain the complex permittivity and permeability of unknown thins film materials. The method is validated for unknown materials that having the following properties: dielectric material losses, dielectric material with losses, and magneto-dielectric material with loss, deposited on a substrate with known dielectric properties. Full wave electromagnetic simulations are used to obtain the S parameters of the structure as a function of frequency [2], which are used with conformal mapping technique CMT [3] to calculate the complex permittivity and permittivity of the unknown materials. Results shown that, the parameters of the material extracted are accurate with an error of 5% for the real and imaginary values, in comparison with the values specified on [1GHz 3 GHz]. This proposed method, will prove to be useful for measuring the complex permittivity and permeability of thin films for a wide range of applications.Voir les détails

Mots clés : GCPWG structures, thin film, dielectric material, CMT

Fast Adapting Mixture Parameters Schemes forProbability Density Di erence-based DeformableModel

Aicha Baya Goumeidane, Nafaa Nacereddine (2018)
Article de conférence

This paper presents a new region-driven active contour usingthe pdf di erence to evolve. The pdf estimation is done via a new andfast Gaussian mixture model (GMM) parameters updating scheme. Theexperiments performed on synthetic and X-ray images have shown notonly an accurate contour delineation but also outstanding performancein terms of execution speed compared to the GMM estimation based onEM algorithm and to non-parametric pdf estimations.Voir les détails

Mots clés : Active contour, Adaptive mixture, GMM parameters up-dates.

Spatially Varying Weighting Function-BasedGlobal and Local Statistical Active Contours.Application to X-Ray Images

Aicha Baya Goumeidane, Nafaa Nacereddine (2016)
Article de journal

Image segmentation is a crucial task in the image processingfield. This paper presents a new region-based active contour whichhandles global information as well as local one, both based on the pixelsintensities. The trade-off between these information is achieved by aspatially varying function computed for each contour node location. Theapplication preliminary results of this method on computed tomographyand X-ray images show outstanding and efficient object extractionVoir les détails

Mots clés : image segmentation, Active contour, Averaged Shifted, histogram, pressure forces, statistics, Spatially varying function

Microstrip Antenna Synthesis using an Application Programming Interface

I. BOUCHACHI, A. Reddaf, K. FERROUDJI, M. Boudjerda, K. Hamdi-Cherif, S .Satta (2018)
Article de conférence

For the synthesis or the modeling of passive microwave structures like antennas, filters, adapters...etc, the simulation plays a very important role. It allows us to get precise estimation of the structure response without having to realize it. In order to synthesis a micro-strip antenna, we create an Application Programming Interface (API) between two softwares. The first one is MATLAB and the second is Ansys HFSS. The error rate between obtained and desired results is used to estimate the optimal dimensions of the structure using Practical Swarm Optimization technique. This method proofs to be effective in synthesizing a micro-strip antenna even for complicated geometry.Voir les détails

Mots clés : Application Programming Interface, Microstrip antenna, Optimization Algorithm

Comparative study between EKF and Geometrical methods for the Acoustic Emission source localization

El yamine DRIS, R. Drai, M. Bentahar, D. Berkani, A. BENAMMAR (2018)
Article de conférence

The purpose of this paper is to optimize and apply probabilistic methods and compare the obtained results to geometric method for locating acoustic emission (AE) source in a plate-like structure. The time of arrival (TOA) of the AE waves in each sensor taking into account the uncertainties, was determined by the continuous wavelet transform (CWT). Then the group wave's velocity was calculated by Monte Carlo simulation. As a probabilistic method, the extended Kalman filter (EKF) is used to iteratively estimate the location of AE sources. Experimental results have shown that the probabilistic method estimates the location of the pencil lead break better than the geometric method.Experimental tests were performed on a copper plate to validate the comparison of the two approaches performances.Voir les détails

Mots clés : Acoustic Emission (AE), Time of arrival (TOA), continuous wavelet transform, Monte Carlo simulation, Geometrical method, Extended Kalman Filter (EKF)

Micrographic Image Segmentation using Level SetModel based on Possibilistic C-MeansClustering

N. Chetih, N. Ramou, Z. MESSALIi, A. SERIR, Y. Boutiche (2017)
Article de journal

Image segmentation is often required as afundamental stage in microstructure material characterization.The objective of this work is to choose hybridization betweenthe Level Set method and the clustering approach in order toextract the characteristics of the materials from thesegmentation result of the micrographic images. Morespecifically, the proposed approach contains two successivenecessary stages. The first one consists in the application ofpossibilistic c-means clustering approach (PCM) to get thevarious classes of the original image. The second stage isbased on using the result of the clustering approach i.e. oneclass among the three existing classes (which interests us) asan initial contour of the level set method to extract theboundaries of interest region. The main purpose of using theresult of the PCM algorithm as initial step of the level setmethod is to enhance and facilitate the work of the latter. Ourexperimental results on real micrographic images show thatthe proposed segmentation method can extract successfully theinterest region according to the chosen class and confirm itsefficiency for segmenting micrographic images of materials.Voir les détails

Mots clés : Level set, clustering approach, micrographic images;, image segmentation.

Robust fuzzy c-means clustering algorithmusing non-parametric Bayesian estimation in wavelet transform domain for noisy MR brain image segmentation

N. Chetih, Z. Messali, A. SERIR, N. Ramou (2018)
Article de journal

The major drawback of the fuzzy c-means (FCM) algorithm is its sensitivity to noise. The authors propose a new extended FCM algorithm based a non-parametric Bayesian estimation in the wavelet transform domain for segmenting noisy MR brain images. They use the Bayesian estimator to process the noisy wavelet coefficients. Before segmentation based on FCM algorithm, they use an a priori statistical model adapted to the modelisation of the wavelet coefficients of a noisy image.The main objective of this wavelet-based Bayesian statistical estimation is to recover a good quality image, from a noisy imageof poor quality. Experimental results on simulated and real magnetic resonance imaging brain images show that their proposed method solves the problem of sensitivity to noise and offers a very good performance that out performs some FCM-based algorithms.Voir les détails

Mots clés : fuzzy C-means algorithm, Non-Parametric Bayesian Estimation, Wavelet transform, image segmentation, MR Brain Images