Search results for " Vision"

showing 10 items of 2709 documents

A-Codes from Rational Functions over Galois Rings

2006

In this paper, we describe authentication codes via (generalized) Gray images of suitable codes over Galois rings. Exponential sums over these rings help determine--or bound--the parameters of such codes.

Discrete mathematicsMathematics::Commutative AlgebraApplied MathematicsFundamental theorem of Galois theoryGalois groupRational functionExponential polynomialComputer Science ApplicationsEmbedding problemDifferential Galois theorysymbols.namesakeGalois rings Gray map codesComputer Science::Computer Vision and Pattern RecognitionComputingMethodologies_SYMBOLICANDALGEBRAICMANIPULATIONComputer Science::MultimediasymbolsSettore MAT/03 - GeometriaGalois extensionResolventMathematicsDesigns, Codes and Cryptography
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Tensor product multiresolution analysis with error control for compact image representation

2002

A class of multiresolution representations based on nonlinear prediction is studied in the multivariate context based on tensor product strategies. In contrast to standard linear wavelet transforms, these representations cannot be thought of as a change of basis, and the error induced by thresholding or quantizing the coefficients requires a different analysis. We propose specific error control algorithms which ensure a prescribed accuracy in various norms when performing such operations on the coefficients. These algorithms are compared with standard thresholding, for synthetic and real images.

Discrete mathematicsMultiresolution analysisMathematicsofComputing_NUMERICALANALYSISWavelet transformImage processingReal imageThresholdingTensor productControl and Systems EngineeringSignal ProcessingComputer Vision and Pattern RecognitionElectrical and Electronic EngineeringChange of basisAlgorithmSoftwareMathematicsImage compressionSignal Processing
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Discrete wavelet transform based multispectral filter array demosaicking

2013

International audience; The idea of colour filter array may be adapted to multi-spectral image acquisition by integrating more filter types into the array, and developing associated demosaicking algorithms. Several methods employing discrete wavelet transform (DWT) have been proposed for CFA demosaicking. In this work, we put forward an extended use of DWT for mul-tispectral filter array demosaicking. The extension seemed straightforward, however we observed striking results. This work contributes to better understanding of the issue by demonstrating that spectral correlation and spatial resolution of the images exerts a crucial influence on the performance of DWT based demosaicking.

Discrete wavelet transformDWT based demosaickingHyperspectral imagingComputer scienceMultispectralMultispectral image[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technologymultispectral filter array demosaicking01 natural sciencesfilter array[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processingimage colour analysis[ INFO.INFO-TI ] Computer Science [cs]/Image Processing0202 electrical engineering electronic engineering information engineeringComputer visionOptical filterImage resolutionimage segmentationDemosaicingmultispectral image acquisitionHyperspectral imagingimagingspectral correlationCorrelationCFA demosaicking[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]020201 artificial intelligence & image processing[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingImage color analysis010309 optics0103 physical sciencesoptical filtersArraysspatial images resolution[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingdiscrete wavelet transformbusiness.industryImage segmentationBinary treesDiscrete wavelet transformscolour filter arrayspectral analysisInterpolationdemosaickingFilter (video)Artificial intelligencebusinessimage resolution
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NIR and Visible Image Fusion for Improving Face Recognition at Long Distance

2014

Face recognition performance achieves high accuracy in close proximity. However, great challenges still exist in recognizing human face at long distance. In fact, the rapidly increasing need for long range surveillance requires a passage from close-up distances to long distances which affects strongly the human face image quality and causes degradation in recognition accuracy. To address this problem, we propose in this paper, a multispectral pixel level fusion approach to improve the performance of automatic face recognition at long distance. The main objective of the proposed approach is to formulate a method to enhance the face image quality as well as the face recognition rate. First, v…

Discrete wavelet transformImage fusionPixelImage qualityComputer sciencebusiness.industryMultispectral imageComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONFacial recognition systemFace (geometry)Singular value decompositionComputer visionArtificial intelligencebusiness
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Multiscale Edges Detection by Wavelet Transform for Model of Face Recognition

1996

Publisher Summary The linear auto-associator is a particular case of the linear-associator. The goal of this network is to associate a set of stimuli to itself, which could be used to store and retrieve face images and it also could be applied as a pre-processing device to simulate some psychological tasks—such as categorizing face according to their gender. A technique of learning based on the wavelet transform can improve recognition capability when the pattern images are with a great noise. One of the ways to store and recall face images uses the linear auto-associative memory. This connectionist model is in conjunction with a pixel-based coding of the faces. The image processing using t…

Discrete wavelet transformLifting schemePixelComputer sciencebusiness.industrySecond-generation wavelet transformComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONWavelet transformPattern recognitionImage processingFacial recognition systemWaveletComputer visionArtificial intelligencebusiness
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Regularization of optical flow with M-band wavelet transform

2003

The optical flow is an important tool for problems arising in the analysis of image sequences. Flow fields generated by various existing solving techniques are often noisy and partially incorrect, especially near occlusions or motion boundaries. Therefore, the additional information on the scene gained from a sequence of images is usually worse. In this paper, discrete wavelet transform has been adopted in order to enhance the reliability of optical flow estimation. A generalization of the well-known dyadic orthonormal wavelets to the case of the dilation scale factor M > 2 with N vanishing moments has been used, and it has proved to be a useful regularizing tool. The advantages in the comp…

Discrete wavelet transformM-band waveletLifting schemebusiness.industryStationary wavelet transformOptical flowComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONWavelet transformWavelet packet decompositionApplied MathematicSettore MAT/08 - Analisi NumericaComputational MathematicsWaveletComputational Theory and MathematicsMultiresolution analysis (MRA)Modeling and SimulationModelling and SimulationComputational MathematicComputer visionArtificial intelligenceHarmonic wavelet transformFast wavelet transformbusinessAlgorithmMathematicsComputers & Mathematics with Applications
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172 REAL TIME EDGES DETECTION USING WAVELET TRANSFORM

2000

One of the way to extract edges uses the fast wavelet transform algorithm. This technique allows the detection of multiscale edges and is used to detect all the details, which are in a picture by modifying the scale. The real time application for edge detection involves the implementation of the algorithm on an integrated circuit like a FPGA and the development of an appropriated board. This article deals about the implementation of a wavelet transform algorithm onto a FPGA and development of an electronic board to detect multiscale edges.

Discrete wavelet transformbusiness.industryComputer scienceSecond-generation wavelet transformStationary wavelet transformWavelet transformWavelet packet decompositionComputer Science::Hardware ArchitectureWaveletComputer visionArtificial intelligenceHarmonic wavelet transformFast wavelet transformbusinessJournal of the Visualization Society of Japan
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EMG artifacts removal during electrical stimulation, a CWT based technique

2014

International audience; A technique of artifacts removal based on the continuous wavelet transform is presented. It uses common mother wavelets to find the temporal localization of stimulation artifacts on electromyogram (EMG) signal during an electrically evoked contraction of a muscle. This method can be used with standard stimulation pulse waveforms like monophasics or biphasics ones. It uses a histogram representation to find the best threshold to apply on the CWT domain. The algotithm is presented with Haar wavelet and then it is used with common wavelet famillies such as Daubechies or Symlets.

Discrete wavelet transformstimulation artifacts0206 medical engineering02 engineering and technologyElectromyography[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing03 medical and health sciences0302 clinical medicineWaveletHistogramwaveletmedicineSource separationWaveformComputer visionContinuous wavelet transformMathematics[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing030222 orthopedicsmedicine.diagnostic_testbusiness.industryhistogram representationPattern recognition020601 biomedical engineeringHaar waveletElectromyogram[SPI.TRON]Engineering Sciences [physics]/Electronics[ SPI.TRON ] Engineering Sciences [physics]/Electronicssource separationArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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A coupled Finite Volume–Smoothed Particle Hydrodynamics method for incompressible flows

2016

Abstract An hybrid approach is proposed which allows to combine Finite Volume Method (FVM) and Smoothed Particle Hydrodynamics (SPH). The method is based on the partitioning of the computational domain into a portion discretized with a structured grid of hexahedral elements (the FVM-domain ) and a portion filled with Lagrangian particles (the SPH-domain ), separated by an interface made of triangular elements. A smooth transition between the solutions in the FVM and SPH regions is guaranteed by the introduction of a layer of grid cells in the SPH-domain and of a band of virtual particles in the FVM one (both neighboring the interface), on which the hydrodynamic variables are obtained throug…

DiscretizationSPHComputational MechanicsGeneral Physics and AstronomyCoupled FVM–SPH approachBoundary condition01 natural sciences010305 fluids & plasmasSettore ICAR/01 - IdraulicaSmoothed-particle hydrodynamicsPhysics and Astronomy (all)0103 physical sciencesComputational mechanicsMechanics of Material0101 mathematicsMirror particleComputational MechanicPhysicsFinite volume methodMechanical EngineeringMathematical analysisSmoothed Particle HydrodynamicComputer Science Applications1707 Computer Vision and Pattern RecognitionGridComputer Science ApplicationsComputational physics010101 applied mathematicsMechanics of MaterialsCompressibilityReduction (mathematics)Interpolation
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Distributed Learning Automata-based S-learning scheme for classification

2019

This paper proposes a novel classifier based on the theory of Learning Automata (LA), reckoned to as PolyLA. The essence of our scheme is to search for a separator in the feature space by imposing an LA-based random walk in a grid system. To each node in the grid, we attach an LA whose actions are the choices of the edges forming a separator. The walk is self-enclosing, and a new random walk is started whenever the walker returns to the starting node forming a closed classification path yielding a many-edged polygon. In our approach, the different LA attached to the different nodes search for a polygon that best encircles and separates each class. Based on the obtained polygons, we perform …

Distributed learningLearning automataComputer sciencePolygonsFeature vector020207 software engineering02 engineering and technologyGridRandom walkVDP::Matematikk og Naturvitenskap: 400::Informasjons- og kommunikasjonsvitenskap: 420Learning automataSupport vector machinesymbols.namesakeArtificial IntelligenceKernel (statistics)Polygon0202 electrical engineering electronic engineering information engineeringGaussian functionsymbols020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionClassificationsAlgorithmPattern Analysis and Applications
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