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Search Results: 1 - 10 of 401221 matches for " M. Bourennane "
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Design of Hardware Accelerators for Content Based Video Indexing
A.Ben Abdelali,A. Mtibaa,E. Bourennane,M. Abid
Asian Journal of Information Technology , 2012,
Abstract: Content based video indexing is currently employed in variety of new applications, including video surveillance, Access to real time incoming video, intelligent transmission of video data, etc. Several methods aiming at automating this time and resource consuming process have appeared in literature. They employ several content analysis and feature extraction techniques including, typically, signal and image processing techniques to analyze color, texture, form, sound, etc. Implementing such applications on a general purpose computer can be easier, but not sufficient to support the complexity and the performance needs of some new applications. The use of application specific hardware permits to offer much greater speed and performance. In this study we focus on hardware implementation of content based video indexing techniques by using the FPGA technology. We aim to propose hardware modules that can satisfy requirements of applications under hard constraints, such as real time applications and applications of high complexity. We represent tow examples of micro-architectures related to the dominant colors descriptor and the compact color descriptor. The synthesis and simulation results for the provided solutions are also given.
Automatic Hardware Implementation Tool for a Discrete Adaboost-Based Decision Algorithm
Mitéran J,Matas J,Bourennane E,Paindavoine M
EURASIP Journal on Advances in Signal Processing , 2005,
Abstract: We propose a method and a tool for automatic generation of hardware implementation of a decision rule based on the Adaboost algorithm. We review the principles of the classification method and we evaluate its hardware implementation cost in terms of FPGA's slice, using different weak classifiers based on the general concept of hyperrectangle. The main novelty of our approach is that the tool allows the user to find automatically an appropriate tradeoff between classification performances and hardware implementation cost, and that the generated architecture is optimized for each training process. We present results obtained using Gaussian distributions and examples from UCI databases. Finally, we present an example of industrial application of real-time textured image segmentation.
Experimental demonstration of universal symmetric quantum telecloning
S. Gaertner,J. Lau,N. Kiesel,M. Bourennane,H. Weinfurter
Physics , 2009,
Abstract: Quantum telecloning is a multiparty quantum communication protocol which allows quantum information broadcasting. It can be, therefore, seen as a generalization of quantum teleportation. However, in contrast to quantum teleportation, it requires the resource of multipartite entanglement. Here we present an experimental demonstration of universal symmetric 1->2 quantum telecloning of qubits via four-photon polarisation entanglement.
Certainty relations between local and nonlocal observables
R. Garcia Diaz,J. L. Romero,G. Bjork,M. Bourennane
Physics , 2005, DOI: 10.1088/1367-2630/7/1/256
Abstract: We demonstrate that for an arbitrary number of identical particles, each defined on a Hilbert-space of arbitrary dimension, there exists a whole ladder of relations of complementarity between local, and every conceivable kind of joint (or nonlocal) measurements. E.g., the more accurate we can know (by a measurement) some joint property of three qubits (projecting the state onto a tripartite entangled state), the less accurate some other property, local to the three qubits, become. We also show that the corresponding complementarity relations are particularly tight for particles defined on prime dimensional Hilbert spaces.
Experimental demonstration of four-party quantum secret sharing
S. Gaertner,C. Kurtsiefer,M. Bourennane,H. Weinfurter
Physics , 2006, DOI: 10.1103/PhysRevLett.98.020503
Abstract: Secret sharing is a multiparty cryptographic task in which some secret information is splitted into several pieces which are distributed among the participants such that only an authorized set of participants can reconstruct the original secret. Similar to quantum key distribution, in quantum secret sharing, the secrecy of the shared information relies not on computational assumptions, but on laws of quantum physics. Here, we present an experimental demonstration of four-party quantum secret sharing via the resource of four-photon entanglement.
Experimental observation of four-photon entanglement from down-conversion
M. Eibl,S. Gaertner,M. Bourennane,Ch. Kurtsiefer,M. Zukowski,H. Weinfurter
Physics , 2003, DOI: 10.1103/PhysRevLett.90.200403
Abstract: We observe polarization-entanglement between four photons produced from a single down-conversion source. The non-classical correlations between the measurement results violate a generalized Bell inequality for four qubits. The characteristic properties and its easy generation with high interferometric contrast make the observed four-photon state well-suited for implementing advanced quantum communication schemes such as multi-party quantum key distribution, secret sharing and telecloning.
About Classification Methods Based on Tensor Modelling for Hyperspectral Images
Salah Bourennane,Caroline Fossati
International Journal of Signal Processing, Image Processing and Pattern Recognition , 2010,
Abstract: Denoising and Dimensionality Reduction (DR) are key issue to improve the classifiers efficiency for Hyper spectral images (HSI). The multi-way Wiener filtering recently developed is used, Principal and independent component analysis (PCA; ICA) and projection pursuit(PP) approaches to DR have been investigated. These matrix algebra methods are applied on vectorized images. Thereof, the spatial rearrangement is lost. To jointly take advantage of the spatial and spectral information, HSI has been recently represented as tensor. Offering multiple ways to decompose data orthogonally, we introduced filtering and DR methods based on multilinear algebra tools. The DR is performed on spectral way using PCA, or PP joint to an orthogonal projection onto a lower subspace dimension of the spatial ways. Weshow the classification improvement using the introduced methods in function to existing methods. This experiment is exemplified using real-world HYDICE data. Multi-way filtering, Dimensionality reduction, matrix and multilinear algebra tools, tensor processing.
Multiway Filtering Based on Multilinear Algebra Tools
Salah Bourennane,Caroline Fossati
International Journal of Signal Processing, Image Processing and Pattern Recognition , 2010,
Abstract: This paper presents some recent filtering methods based on the lower-rank tensor approximation approach for denoising tensor signals. In this approach, multicomponent data are represented by tensors, that is, multiway arrays, and the presented tensor filtering methods rely on multilinear algebra. First, the classical channel-by-channel SVD-based filtering method is overviewed. Then, an extension of the classical matrix filtering method is presented. It is based on the lower rank- K ,...,Kn 1 truncation of the HOSVD which performsa multimode Principal Component Analysis (PCA) and is implicitly developed for an additive white Gaussian noise. Two tensor filtering methods recently developed by the authors are also overviewed. The performances and comparative results between all these tensor filtering methods are presented for the cases of noise reduction in color images.
Array Processing and Fast Optimization Algorithms for Distorted Circular Contour Retrieval
Julien Marot,Salah Bourennane
EURASIP Journal on Advances in Signal Processing , 2007, DOI: 10.1155/2007/57354
Abstract: A specific formalism for virtual signal generation permits to transpose an image processing problem to an array processing problem. The existing method for straight-line characterization relies on the estimation of orientations and offsets of expected lines. This estimation is performed thanks to a subspace-based algorithm called subspace-based line detection (SLIDE). In this paper, we propose to retrieve circular and nearly circular contours in images. We estimate the radius of circles and we extend the estimation of circles to the retrieval of circular-like distorted contours. For this purpose we develop a new model for virtual signal generation; we simulate a circular antenna, so that a high-resolution method can be employed for radius estimation. An optimization method permits to extend circle fitting to the segmentation of objects which have any shape. We evaluate the performances of the proposed methods, on hand-made and real-world images, and we compare them with generalized Hough transform (GHT) and gradient vector flow (GVF).
Contour Estimation by Array Processing Methods
Bourennane Salah,Marot Julien
EURASIP Journal on Advances in Signal Processing , 2006,
Abstract: This work is devoted to the estimation of rectilinear and distorted contours in images by high-resolution methods. In the case of rectilinear contours, it has been shown that it is possible to transpose this image processing problem to an array processing problem. The existing straight line characterization method called subspace-based line detection (SLIDE) leads to models with orientations and offsets of straight lines as the desired parameters. Firstly, a high-resolution method of array processing leads to the orientation of the lines. Secondly, their offset can be estimated by either the well-known method of extension of the Hough transform or another method, namely, the variable speed propagation scheme, that belongs to the array processing applications field. We associate it with the method called "modified forward-backward linear prediction" (MFBLP). The signal generation process devoted to straight lines retrieval is retained for the case of distorted contours estimation. This issue is handled for the first time thanks to an inverse problem formulation and a phase model determination. The proposed method is initialized by means of the SLIDE algorithm.
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