Electronique

Nombre total de résultats : 521
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Impact of the inhomogeneous structure of the active layer on the transfer characteristic of polysilicon TFT's

Hadjira Tayoub, asmaa bensmain, Baya Zebentout, Zineb Benamara (2012)
Article de journal

Recently polycrystalline silicon (pc-Si) thin film transistors (TFT's) have emerged as the devices of choice for many applications. The TFT's made of a thin un-doped polycrystalline silicon film deposited on a glass substrate by the Low Pressure Chemical Vapor Deposition technique LPCVD have limits in the technological process to the temperature <; 600°C. The benefit of pc-Si is to make devices with large grain size. Unfortunately, according to the conditions during deposition, the pc-Si layers can consist of a random superposition of grains of different sizes, where grains boundaries parallels and perpendiculars appear. In this paper, the transfer characteristics IDS-VGS are simulated by solving a set of two-dimensional (2D) drift-diffusion equations together with the usual density of states (DOS: exponential band tails and Gaussian distribution of dangling bonds) localized at the grains boundaries. The impact of thickness of the active layer on the distribution of the electrostatic potential, the effect of density of intergranular traps states and grain size on the TFT's transfer characteristics IDS-VGS have been also investigated.Voir les détails

Mots clés : Transistor TFT, 2D simulation, heterogeneous structure, Grain Size, transfer characteristic

Multiple classifier combination for steel surface inspection

Rachid Zaghdoudi, Hamid Seridi, Adel BOUDIAF (2019)
Article de conférence

Vision-based steel surface inspection systems have gained increasing interest over the two past decades because they offer the possibility to meet the requirements of manufacturers in terms of time, cost and accuracy compared to traditional methods based on human vision. The main objective of this paper is to propose an efficient inspection system based on machine vision technology and multiple classifier combination to detect and classify the different types of defects in steel products. This system is based on two independent classifiers, support vector machine (SVM) and fuzzy K-nearest neighbor (FKNN). Features are extracted with the gray level co-occurrence matrix (GLCM) and Histogram of Oriented Gradients (HOG). Principal Component Analysis (PCA) is applied to these features in order to reduce the descriptor size and avoid over-fitting resulting from features redundancy. Each set of features is respectively inputted to SVM and FKNN to form four parallel classifiers. Also, seven fusion rules are applied to give the final decision. To evaluate the performance of the proposed system, a series of experiments was conducted on the NEU Surface Defects database. The results obtained demonstrate the effectiveness of the proposed approach for classifying steel surface defects.Voir les détails

Mots clés : machine vision, classifier combination, surface defects, support vector machine (SVM), fuzzy K-nearest neighbor (FKNN), histogram of oriented gradients (HOG), gray level co-occurrence matrix (GLCM)

SIMULATION BIDIMENSIONNELLE DU TRANSISTOR MOS EN SILICIUM DEPOSE PAR LES TECHNIQUES BASSES TEMPERATURES

TAYOUB Hadjira (2011)
Mémoire de magister

L’objectif du thème proposé est consacré à une étude sur la construction d’une structure hétérogène de silicium polycristallin permettant de rendre compte les caractéristiques courant-tension du transistor MOSà canal N fabriqué à base de ce matériau. La couche de silicium polycristallin réelle contient de grain et de jointsde grain répartis aléatoirement. Donc pour modéliser plus simplement cette couche, un modèle géométrique 2Dà permet la mise en évidence d’un certain nombre de joints de grain perpendiculaires et parallèles à la surfacede croissance.Pour cela, une simulation approfondie basée sur la résolution numérique, à deux dimensions, des équationsdécrivant le transport dans les dispositifs à semi-conducteurs (équation de Poisson et les deux équationsde continuité des électrons et des trous) est utilisée en tenant en compte de la particularité des propriétés électriqueset physiques du silicium polycristallin. Dans cette simulation, on analyse la sensibilité des caractéristiques de transfert IDS(VGS) en fonction de la structure granulaire du canal, le nombre de joints de grains, défauts intergranulaires et à l’interface etc… Voir les détails

Mots clés : Silicium polycristallin, Structure hétérogène, Transistor TFT, Techniques basses températures, Simulation numérique 2D

Unsupervised weld defect classification in radiographic images using multivariate generalized Gaussian mixture model with exact computation of mean and shape parameters

Nafaa Nacereddine, Aicha Baya Goumeidane, Djemel Ziou (2019)
Article de journal

In industry, the welding inspection is considered as a mandatory stage in the process of quality assurance/quality control. This inspection should satisfy the requirements of the standards and codes governing the manufacturing process in order to prevent unfair harm to the industrial plant in construction. For this purpose, in this paper, a software specially conceived for computer-aided diagnosis in weld radiographic testing is presented, where a succession of operations of preprocessing, image segmentation, feature extraction and finally defects classification is carried out on radiographic images. The last operation which is the main contribution in this paper consists in an unsupervised classifier based on a finite mixture model using the multivariate generalized Gaussian distribution (MGGD). This classifier is newly applied on a dataset of weld defect radiographic images. The parameters of the nonzero-mean MGGD-based mixture model are estimated using the Expectation-Maximization algorithm where, exact computations of mean and shape parameters are originally provided. The weld defect database represent four weld defect types (crack, lack of penetration, porosity and solid inclusion) which are indexed by a shape geometric descriptor composed of geometric measures. An outstanding performance of the proposed mixture model, compared to the one using the multivariate Gaussian distribution, is shown, where the classification rate is improved by 3.2% for the whole database, to reach more than 96%. The efficiency of the proposed classifier is mainly due to the flexible fitting of the input data, thanks to the MGGD shape parameter.Voir les détails

Mots clés : Mixture model, Multivariate GGD, radiography, weld defect, classification

Fast Adapting Mixture Parameters Schemes for Probability Density Difference-Based Deformable Model

Aicha Baya Goumeidane, Nafaa Nacereddine (2019)
Article de journal

This paper presents a new region-driven active contour using the pdf difference to evolve. The pdf estimation is done via a new and fast Gaussian mixture model (GMM) parameters updating scheme. The experiments performed on synthetic and X-ray images have shown not only an accurate contour delineation but also outstanding performance in terms of execution speed compared to the GMM estimation based on EM algorithm and to non-parametric pdf estimations.Voir les détails

Mots clés : Active contour, Adaptive mixture, GMM parameters update

Missing data restoration of sinogram in limited-angle computed tomography

a.benammar, a.allag, N.Mazouz, R.Drai, M.Yahi (2019)
Article de conférence

We present in this work the limited-angle computed tomography, which is an ill-posed inversion problem. This case often exists in the industry to allow faster non-destructive testing during production phase. However, the inspection is difficult to achieve due to the shape and size of the inspected parts. During the last decade, various approaches were proposed for case of limited-angle. These methods were developed for medical application use and do not take into account physical limitations specific to industrial materials. The aim of this work is to propose a method, which permits to recover the missing data in the acquisition of projections using minimizing a function. We tested our method with sinogram obtained from Shepp-Logan phantom containing missing projections. The reconstruction image of inpainted sinogram achived using FBP method and Iterative cimmino method. The results clearly show that the proposed method can retrieve accurate information that leads to a better-reconstructed image.Voir les détails

Mots clés : image reconstruction, FBP, Cimmino, Inpainting, Missing projections

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)
Article de journal

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

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.