Search results for "Signal and Image processing"

showing 10 items of 454 documents

Pattern dynamics in a nonlinear electrical lattice

2003

International audience; In this paper, we present experiments using a nonlinear electrical line, modeling the FitzHugh-Nagumo equation, without recovery term. Different patterns are studied according to the para meters of this medium and initial conditions. We then propose to apply these results to the domain of signal processing. We show that erosion and dilation of a binary signal, two kinds,of binarization-one depending on an amplitude threshold, the other on an energetical threshold-and nonlinear filtering allowing noise removal can be obtained in the same medium.

Signal processing[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingNonlinear filteringApplied MathematicsMathematical analysis[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing01 natural sciencesBinary signal010305 fluids & plasmasNonlinear systemAmplitude[NLIN.NLIN-PS]Nonlinear Sciences [physics]/Pattern Formation and Solitons [nlin.PS][INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingControl theoryModeling and SimulationLattice (order)0103 physical sciences[ NLIN.NLIN-PS ] Nonlinear Sciences [physics]/Pattern Formation and Solitons [nlin.PS]010306 general physicsNoise removalEngineering (miscellaneous)[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingMathematics
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Complexity analysis of experimental cardiac arrhythmia

2014

International audience; To study the cardiac arrhythmia, an in vitro experimental model and Multielectrodes Array (MEA) are used. This platform serves as an intermediary of the electrical activities of cardiac cells and the signal processing / dynamics analysis. Through it the extracellular potential of cardiac cells is acquired, allowing a real-time monitoring / analyzing. Since MEA has 60 electrodes / channels dispatched in a rectangular region, it allows real-time monitoring and signal acquisition on multiple sites. The in vitro experimental model (cardiomyocytes cultures from new-born rats' heart) is directly prepared on the MEA. This carefully prepared culture has similar parameters as…

Signal processing[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputer scienceCardiac arrhythmiaAtrial fibrillation[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing030204 cardiovascular system & hematologymedicine.disease01 natural sciencesApproximate entropySignal acquisitionSample entropy03 medical and health sciencesExtracellular potential0302 clinical medicine[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing0103 physical sciencesmedicinecardiovascular systemEntropy (information theory)010306 general physics[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingBiomedical engineering
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Energy balance in single exposure multispectral sensors

2013

International audience; Recent simulations of multispectral sensors are based on a simple Gaussian model, which includes filters transmittance and substrate absorption. In this paper we want to make the distinction between these two layers. We discuss the balance of energy by channel in multispectral solid state sensors and propose an updated simple Gaussian model to simulate multispectral sensors. Results are based on simulation of typical sensor configurations.

SiliconMaterials science[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processingoptical sensorsChannel (digital image)Equations[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingMultispectral imageComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONPhotodetectorGaussian processes02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing01 natural sciences010309 opticssymbols.namesakeMathematical model[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing0103 physical sciences0202 electrical engineering electronic engineering information engineeringTransmittanceComputer Science::Networking and Internet ArchitectureSpectral and color filter arraysoptical filtersOptical filterGaussian processPhysics::Atmospheric and Oceanic Physics[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingRemote sensingtransmittance filterSubstratesSensorsGaussian modelmultispectral solid state sensorCamerasenergy balancespectral analysisConvolutionexposure multispectral sensorComputer Science::Computer Vision and Pattern Recognitionsubstrate absorptionlight absorptionlight sensorsymbolstransmittance filters020201 artificial intelligence & image processingGaussian network model[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingEnergy (signal processing)
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3D objects descriptors methods: Overview and trends

2017

International audience; Object recognition or object's category recognition under varying conditions is one of the most astonishing capabilities of human visual system. The scientists in computer vision have been trying for decades to reproduce this ability by implementing algorithms and providing computers with appropriate tools. Hence, several intelligent systems have been proposed. To act in this field, numerous approaches have been proposed. In this paper we present an overview of the current trend in 3D objects recognition and describe some representative state of the art methods, highlighting their limits and complexity.

Sketch recognitionComputer science3D single-object recognition[INFO.INFO-GR] Computer Science [cs]/Graphics [cs.GR]02 engineering and technology[INFO.INFO-CG]Computer Science [cs]/Computational Geometry [cs.CG]Field (computer science)object recognitionhuman visual systemcomputer vision[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingHuman–computer interactionobject category recognition0202 electrical engineering electronic engineering information engineeringskeletonComputer vision3D objects descriptors methodsVisualization3D objects recognitionintelligent systemsNon-Controlled Indexingbusiness.industryCognitive neuroscience of visual object recognitionIntelligent decision support system[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Shape020207 software engineeringComputational modelingObject (computer science)Keypoints3D objects[INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR]VisualizationRecognition[INFO.INFO-CG] Computer Science [cs]/Computational Geometry [cs.CG]Human visual system modelSolid modelingThree-dimensional displays020201 artificial intelligence & image processingArtificial intelligencebusiness
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A new weighted normal-based filter for 3D mesh denoising

2018

In this paper, we propose a normal based filtering method for 3D mesh denoising. For this purpose, we compute the new triangle normal vectors by using a weighted sum of the average (smoothness) and the myriad (sharpness) filters in each neighborhood. These weights, that reflect the degree of the surface sharpness, are calculated according to the statistical distribution of the angles between the normal vectors of the triangles. The histogram of the angles between surface normal vectors is accurately fitted by the well known Cauchy distribution. Here, we justify the use of the myriad filter whose estimated value represents the optimum of the location parameter of the investigated distributio…

Smoothness (probability theory)Location parameter[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingCauchy distribution020206 networking & telecommunications020207 software engineering02 engineering and technologyFilter (signal processing)Hausdorff distance[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingHistogram0202 electrical engineering electronic engineering information engineeringPolygon meshNormalAlgorithmComputingMilieux_MISCELLANEOUSComputingMethodologies_COMPUTERGRAPHICSMathematics2018 9th International Symposium on Signal, Image, Video and Communications (ISIVC)
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UBFC-Phys: A Multimodal Database For Psychophysiological Studies of Social Stress

2021

As humans, we experience social stress in countless everyday-life situations. Giving a speech in front of an audience, passing a job interview, and similar experiences all lead us to go through stress states that impact both our psychological and physiological states. Therefore, studying the link between stress and physiological responses had become a critical societal issue, and recently, research in this field has grown in popularity. However, publicly available datasets have limitations. In this article, we propose a new dataset, UBFC-Phys, collected with and without contact from participants living social stress situations. A wristband was used to measure contact blood volume pulse (BVP…

Social stressFacial expressionModalitiesComputer scienceSpeech recognition010401 analytical chemistryFeature extraction[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]020206 networking & telecommunications02 engineering and technology01 natural sciencesField (computer science)0104 chemical sciencesHuman-Computer InteractionPsychophysiology[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingStress (linguistics)0202 electrical engineering electronic engineering information engineeringTask analysisComputingMilieux_MISCELLANEOUSSoftwareIEEE Transactions on Affective Computing
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A measurement-based channel model for vehicular communications in tunnels

2014

Wireless Communications and Networking Conference (WCNC), 2014 IEEE, Istanbul, TURQUIE, 06-/04/2014 - 09/04/2014; In this paper, we present a new version of the iterative nonlinear least square approximation (INLSA) algorithm for the design of measurement-based channel simulators. The proposed method aims to match the time-variant impulse response (TVIR) of the simulation model to that of the measured channel. The propagation delays are discerned directly from the measurements, whereas the gains, the Doppler frequencies, and the phases are computed iteratively by minimizing a matching error norm. We evaluate the performance of the proposed method in terms of the approximation of the transfe…

Spatial correlationCHANNEL SOUNDINGComputer scienceMIMOITERATIVE OPTIMIZATIONPROPAGATIONCOMMUNICATIONTransfer functionPrecodingTRAITEMENT DU SIGNALTECHNOLOGIE SANS FILChannel capacityImpulse responseSimulationANTENNEEmulationOPTIMISATIONCHANNEL MODELINGMOBILE FADING CHANNELSMODELISATIONTUNNELChannel state informationTRANSMISSION DES DONNEESTUNNEL CHANNELSAlgorithm[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingCommunication channel
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Salient Pixels and Dimensionality Reduction for Display of Multi/Hyperspectral Images

2012

International audience; Dimensionality Reduction (DR) of spectral images is a common approach to different purposes such as visualization, noise removal or compression. Most methods such as PCA or band selection use either the entire population of pixels or a uniformly sampled subset in order to compute a projection matrix. By doing so, spatial information is not accurately handled and all the objects contained in the scene are given the same emphasis. Nonetheless, it is possible to focus the DR on the separation of specific Objects of Interest (OoI), simply by neglecting all the others. In PCA for instance, instead of using the variance of the scene in each spectral channel, we show that i…

Spectral Images[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingChannel (digital image)Computer scienceMultispectral image0211 other engineering and technologiesComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingProjection (linear algebra)[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing0202 electrical engineering electronic engineering information engineeringIAPRComputer vision021101 geological & geomatics engineeringSaliencyPixelbusiness.industryDimensionality reductionHyperspectral imagingPattern recognitionDimensionality reductionVisualizationComputer Science::Computer Vision and Pattern Recognition020201 artificial intelligence & image processingArtificial intelligenceFocus (optics)business[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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18F-FDG PET imaging of breast cancer : evaluation of the metabolic behaviour of the different breast cancer subtypes and prediction of the tumor resp…

2015

Positron Emission Tomography (PET) with 18Fluoro-deoxyglucose (18F-FDG) is the reference imaging examination for in-vivo quantification of the glucidic metabolism of tumour cells. It allows for the monitoring of tumour metabolic changes during chemotherapy. Breast cancer comprises several distinct genomic entities with different biological characteristics and clinical behaviours, leading to different tailored treatments. The aim of this doctoral thesis was to evaluate the relationship between the different biological entities of breast cancer and the tumour metabolic behaviour during neoadjuvant chemotherapy. We have also retrieved, among the various metabolic parameters on PET images, the …

Subtypes[SDV.IB] Life Sciences [q-bio]/BioengineeringFDGPositon EmissionTomographyRéponse tumoraleNeoadjuvant chemotherapyPhénotypesPETBreast cancerTEP[SDV.CAN] Life Sciences [q-bio]/CancerÉvaluationTomographie par Emission de PositonChimiothérapie néoadjucanteTumor responseCancer du sein[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
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Classification of SD-OCT volumes with multi pyramids, LBP and HOG descriptors: application to DME detections.

2016

This paper deals with the automated detection of Diabetic Macular Edema (DME) on Optical Coherence Tomography (OCT) volumes. Our method considers a generic classification pipeline with preprocessing for noise removal and flattening of each B-Scan. Features such as Histogram of Oriented Gradients (HOG) and Local Binary Patterns (LBP) are extracted and combined to create a set of different feature vectors which are fed to a linear-Support Vector Machines (SVM) Classifier. Experimental results show a promising sensitivity/specificity of 0.75/0.87 on a challenging dataset.

Support Vector Machinegenetic structuresDatabases FactualComputer science[INFO.INFO-IM] Computer Science [cs]/Medical Imaging02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]01 natural sciences[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]0202 electrical engineering electronic engineering information engineeringImage Processing Computer-AssistedSegmentationComputer visionmedicine.diagnostic_test[ INFO.INFO-IM ] Computer Science [cs]/Medical ImagingDiabetic retinopathyHistogram of oriented gradientsmedicine.anatomical_structure020201 artificial intelligence & image processing[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingTomography Optical CoherenceLocal binary patternsFeature vectorDiabetic macular edemaFeature extractionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processingSensitivity and SpecificityMacular Edema010309 opticsOptical coherence tomographyHistogram0103 physical sciencesmedicine[INFO.INFO-IM]Computer Science [cs]/Medical ImagingHumansMacular edema[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingRetinaDiabetic Retinopathybusiness.industry[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Pattern recognitionImage segmentationmedicine.diseaseeye diseasesSupport vector machineComputingMethodologies_PATTERNRECOGNITIONsense organsArtificial intelligencebusinessAnnual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
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