Nombre total de résultats : 509
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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.

A Bayesian Mumford–Shah Model for Radiography ImageSegmentation

N. Ramou, N. Chetih, M. Halimi  (2018)

This paper investigates the segmentation of radiographic images using a level set method based on a BayesianMumford–Shahmodel. The objective is to separate regions in an image that have very close arithmetic means, where a model based on thestatistical mean is not effective. Experimental results show that the proposed model can successfully separate such regions,in both synthetic images and real radiography images. Voir les détails

Mots clés : Level set

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

Study and modelling of a microwave sensor tocharacterize a dielectric materials and for CNDapplications

Z.GUEZOUI, M.amir, H.Amar  (2018)
Article de conférence

Non-destructive testing is a science of evaluationvarious properties of materials, without compromising itsusefulness and use. These properties can be physical, chemical,mechanical or geometrical. There are several techniques of nondestructive testing such as: acoustic emission, penetrate testing,eddy current, ultrasound and radiography, ... . However, each ofthese methods has certain limitations and disadvantages. Sincethe 1970s, some researchers have tried to use microwavetechniques to detect possible surface cracks in metal components,volumic cracks in dielectric materials or to characterize adielectric material.The objective of this article is to present a method ofcharacterization of dielectric materials, by modeling a microwavesensor. A change in the resonant frequency of the microwavesensor resulting from a change in its effective dielectric constantis considered as an index to define the dielectric constant of thesample. This work was devoted to study, modelling andrealization of a micro strip structure by the method of moments,later this structure will be simulated by a numerical modellingsoftware HFSS (High-Frequency Structure Simulator) to confirmthe results and validate the model. Voir les détails

Mots clés : Non-Destructive testing, Microwave Techniques, HFSS, Microwave Sensor, Dielectric Constant, Micro strip Modelling, moment method

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.

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

Aicha Baya Goumeidane, Nafaa Nacereddine  (2016)

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 extraction Voir les détails

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

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

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

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)

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

Reconnaissance hors ligne des mots arabes manuscrits par les réseaux de neurones

Rachid Zaghdoudi (2008)
Mémoire de magister

Le traitement de l'écrit est un domaine en pleine expansion qui commenceaujourd'hui à voir aboutir certaines réalisations industrielles importantes. Dans cecadre, la reconnaissance hors ligne de l'écriture arabe manuscrite reste cependant undes sujets les plus difficiles et les plus actifs au niveau de la recherche.La difficulté majeure rencontrée lors de la conception d'un système dereconnaissance des mots arabes manuscrits, est le problème de la segmentation de cesmots en caractères en vue de leur reconnaissance, pour remédier à ce problème, nousproposons une méthode globale pour la reconnaissance des mots arabes manuscritsdans un vocabulaire limité. Le système développé s’articule autour de cinq modulesdistincts : Acquisition, prétraitements, segmentation en parties connexes, extractiondes primitives les plus pertinentes et reconnaissance (classification et décision). Cedernier est basé sur les réseaux de neurones de type PMC.Pour tester la fiabilité de ce système de reconnaissance, des expériences ontété effectuées sur une base de données représentant les noms des 48 WilayasAlgériennes. Qui ont montré que l'approche proposée semble une solution intéressanteau problème de la reconnaissance des mots arabes manuscrits. Voir les détails

Mots clés : Reconnaissance d'écriture arabe manuscrite ; approche globale ; extractions des caractéristiques ; réseaux de neurones.

Structural, electronic and optical properties for chalcopyrite semiconducting materials: ab-initio computational study

Moufdi Hadjab, Miloud IBRIR, Smail BERRAH, Hamza ABID, Mohammad Alam Saeed  (2018)

Investigation of the physical properties of chalcopyrite materials using ab-initio methods have been carried out to simulate a new structure of thin-films photovoltaic cells with high conversion efficiency. The Density Functional Theory calculations have been performed using Wien2k computational package by employing the full-potential linearized augmented plane wave method. Structural and electronic properties of chalcopyrite semiconducting material Copper–Indium–Gallium–Selenium i.e. CuIn1-xGaxSe2 have been investigated using local density approximation for the exchange-correlation potential. The electronic structures and linear optical properties have been studied using both the semi-local Becke-Johnson potential and its modified form i.e. mBJ and TB-mBJ. Computational results are in good agreement with those acquired experimentally. The viability of alloys in realization of ultra-thin-film based (CIGS) solar cells with high performance has been proposed after simulation and analysis study using one of solar cell simulation tools. The studied material exhibits capability to become a promising candidate for fabrication of optoelectronic and photovoltaic devices. Voir les détails

Mots clés : Chalcopyrite, FP-LAPW, optical properties, Thin-films solar cells, wien2k