Search results for " pattern"

showing 10 items of 2245 documents

Multispectral Imaging using a Stereo Camera: Concept, Design and Assessment

2011

This paper proposes a one-shot six-channel multispectral color image acquisition system using a stereo camera and a pair of optical filters. The two filters from the best pair selected from among readily available filters such that they modify the sensitivities of the two cameras in such a way that they produce optimal estimation of spectral reflectance and/or color are placed in front of the two lenses of the stereo camera. The two images acquired from the stereo camera are then registered for pixel-to-pixel correspondence. The spectral reflectance and/or color at each pixel on the scene are estimated from the corresponding camera outputs in the two images. Both simulations and experiments…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer scienceMultispectral imageComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONlcsh:TK7800-836002 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing01 natural scienceslcsh:Telecommunicationlaw.inventionMultispectral pattern recognitionstereo camera010309 optics[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessinglawCamera auto-calibrationlcsh:TK5101-67200103 physical sciences0202 electrical engineering electronic engineering information engineeringmultispectral imagingComputer visionreflectance estimationPixelColor imagebusiness.industrylcsh:ElectronicsReflectivityLens (optics)020201 artificial intelligence & image processingArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing:Mathematics and natural science: 400::Information and communication science: 420::Simulation visualization signal processing image processing: 429 [VDP]Stereo cameraComputer stereo visionCamera resectioning
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Reaction-Diffusion Network For Geometric Multiscale High Speed Image Processing

2010

International audience; In the framework of heavy mid-level processing for high speed imaging, a nonlinear bi-dimensional network is proposed, allowing the implementation of active curve algorithms. Usually this efficient type of algorithm is prohibitive for real-time image processing due to its calculus charge and the inadequate structure for the use of serial or parallel architectures. Another kind of implementation philosophy is proposed here, by considering the active curve generated by a propagation phenomenon inspired from biological modeling. A programmable nonlinear reaction-diffusion system is proposed under front control and technological constraints. Geometric multiscale processin…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer scienceNonlinear signal processingImage processing02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingType (model theory)Multiscale geometryComputational scienceImage analysisNonlinear signal processing[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingReaction–diffusion systemDigital image processing0202 electrical engineering electronic engineering information engineeringComputer visionStructure (mathematical logic)Biological modelingbusiness.industry020208 electrical & electronic engineeringNonlinear systemSignal Processing020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Spatially variant dimensionality reduction for the visualization of multi/hyperspectral images

2011

International audience; In this paper, we introduce a new approach for color visu- alization of multi/hyperspectral images. Unlike traditional methods, we propose to operate a local analysis instead of considering that all the pixels are part of the same population. It takes a segmentation map as an input and then achieves a dimensionality reduction adaptively inside each class of pixels. Moreover, in order to avoid unappealing discon- tinuities between regions, we propose to make use of a set of distance transform maps to weigh the mapping applied to each pixel with regard to its relative location with classes' centroids. Results on two hyperspec- tral datasets illustrate the efficiency of…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer sciencePopulation0211 other engineering and technologiesComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing0202 electrical engineering electronic engineering information engineeringComputer visionSegmentationspectral imageseducationspatially variantvisualization021101 geological & geomatics engineeringdimensionality reductioneducation.field_of_studyPixelbusiness.industryDimensionality reductionHyperspectral imagingIndependent component analysisVisualizationComputer Science::Computer Vision and Pattern Recognition020201 artificial intelligence & image processingArtificial intelligencebusinessDistance transform[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Validation of a 2D multispectral camera: application to dermatology/cosmetology on a population covering five skin phototypes

2011

International audience; This paper presents the validation of a new multispectral camera specifically developed for dermatological application based on healthy participants from five different Skin PhotoTypes (SPT). The multispectral system provides images of the skin reflectance at different spectral bands, coupled with a neural network-based algorithm that reconstructs a hyperspectral cube of cutaneous data from a multispectral image. The flexibility of neural network based algorithm allows reconstruction at different wave ranges. The hyperspectral cube provides both high spectral and spatial information. The study population involves 150 healthy participants. The participants are classif…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer sciencePopulationMultispectral imageSkin imaging system[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingspectral reflectance01 natural sciencesspectral reconstructionMultispectral pattern recognition010309 optics030207 dermatology & venereal diseases03 medical and health sciencesFitzpatrick scale0302 clinical medicine[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing0103 physical scienceseducationRemote sensingvalidationeducation.field_of_studyHyperspectral imagingSpectral bandshyperspectral cubemultispectral imageFace (geometry)Cube[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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A nonlinear oscillators network devoted to image processing

2004

A contrast enhancement and image inverting tool using a lattice of uncoupled nonlinear oscillators is proposed. We show theoretically and numerically that the gray scale picture contrast is strongly enhanced even if this one is initially very small. An image inversion can be also obtained in real time with the same Cellular Nonlinear Network (CNN) without reconfiguration of the network. A possible electronic implementation of this CNN is finally discussed.

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer science[ PHYS.COND.CM-DS-NN ] Physics [physics]/Condensed Matter [cond-mat]/Disordered Systems and Neural Networks [cond-mat.dis-nn]Image processing[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingCellular nonlinear networksTopology01 natural sciencesGrayscale010305 fluids & plasmasNonlinear oscillators[NLIN.NLIN-PS]Nonlinear Sciences [physics]/Pattern Formation and Solitons [nlin.PS][INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingControl theoryLattice (order)0103 physical sciences[ NLIN.NLIN-PS ] Nonlinear Sciences [physics]/Pattern Formation and Solitons [nlin.PS][PHYS.COND.CM-DS-NN]Physics [physics]/Condensed Matter [cond-mat]/Disordered Systems and Neural Networks [cond-mat.dis-nn]010306 general physicsEngineering (miscellaneous)ComputingMilieux_MISCELLANEOUSArtificial neural networkApplied MathematicsControl reconfigurationInversion (meteorology)neural networks[ SPI.TRON ] Engineering Sciences [physics]/Electronics[SPI.TRON]Engineering Sciences [physics]/ElectronicsNonlinear systemComputer Science::Computer Vision and Pattern RecognitionModeling and SimulationNonlinear dynamics[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Region-based segmentation on depth images from a 3D reference surface for tree species recognition.

2013

International audience; The aim of the work presented in this paper is to develop a method for the automatic identification of tree species using Terrestrial Light Detection and Ranging (T-LiDAR) data. The approach that we propose analyses depth images built from 3D point clouds corresponding to a 30 cm segment of the tree trunk in order to extract characteristic shape features used for classifying the different tree species using the Random Forest classifier. We will present the method used to transform the 3D point cloud to a depth image and the region based segmentation method used to segment the depth images before shape features are computed on the segmented images. Our approach has be…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer science[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingFeature extractionPoint cloudComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScale-space segmentation[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technology[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Minimum spanning tree-based segmentation[STAT.AP] Statistics [stat]/Applications [stat.AP][INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[ INFO.INFO-TI ] Computer Science [cs]/Image Processing0202 electrical engineering electronic engineering information engineeringSegmentationComputer vision[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing[STAT.AP]Statistics [stat]/Applications [stat.AP]Contextual image classificationbusiness.industry[ STAT.AP ] Statistics [stat]/Applications [stat.AP][INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]020207 software engineeringPattern recognitionImage segmentation15. Life on landdepth image segmentationRandom forestdepth images from 3D point cloudsIEEE[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV][INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]020201 artificial intelligence & image processingsingle tree species recognitionArtificial intelligenceRange segmentationbusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingForest inventory
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Remote Photoplethysmography Based on Implicit Living Skin Tissue Segmentation

2016

International audience; Region of interest selection is an essential part for remote photoplethysmography (rPPG) algorithms. Most of the time, face detection provided by a supervised learning of physical appearance features coupled with skin detection is used for region of interest selection. However, both methods have several limitations and we propose to implicitly select living skin tissue via their particular pulsatility feature. The input video stream is decomposed into several temporal superpixels from which pulse signals are extracted. Pulsatility measure for each temporal superpixel is then used to merge pulse traces and estimate the photoplethysmogram signal. This allows to select …

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer science[SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging[INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing0206 medical engineering[INFO.INFO-IM] Computer Science [cs]/Medical Imaging02 engineering and technology[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]01 natural sciences010309 optics[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingSkin tissueRegion of interestPhotoplethysmogram0103 physical sciences[INFO.INFO-IM]Computer Science [cs]/Medical ImagingSegmentationComputer visionFace detection[ SDV.IB.IMA ] Life Sciences [q-bio]/Bioengineering/Imaging[ INFO.INFO-IM ] Computer Science [cs]/Medical Imagingbusiness.industrySupervised learning[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]020601 biomedical engineering[SDV.IB.IMA] Life Sciences [q-bio]/Bioengineering/ImagingArtificial intelligencebusiness
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Quadratic Objective Functions for Dichromatic Model Parameters Estimation

2017

International audience; In this paper, we present a novel method to estimate dichromatic model parameters from a single color image. Estimation of reflectance, shading and specularity has many applications such as shape recovery, specularity removal and facilitates classical image processing and computer vision tasks such as segmentation or classification. Our method is based on two successive and independent constrained quadratic programming steps to recover the parameters of the model. Compared to recent methods, our approach has the advantage to transform a complex inverse problem into two parralelizable optimization steps that are much easier to solve. We have compared our method with r…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingLinear programmingColor imagebusiness.industry[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]020206 networking & telecommunicationsImage processing02 engineering and technologyInverse problem[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Quadratic equation[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Specularity[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingRobustness (computer science)0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingComputer visionQuadratic programmingArtificial intelligencebusinessAlgorithmMathematics
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Parameter-free adaptive step-size multiobjective optimization applied to remote photoplethysmography

2018

International audience; In this work, we propose to reformulate the objective function of Independent Component Analysis (ICA) to make it a better posed problem in the context of Remote photoplethysmography (rPPG). In recent previous works, linear combination coefficients of RGB channels are estimated maximizing the non-Gaussianity of ICA output components. However, in the context of rPPG a priori knowledge of the pulse signal can be incorporated into the component extraction algorithm. To this end, the contrast function of regular ICA is extended with a measure of periodicity formulated using autocorrelation. This novel semi-blind source extraction method for measuring rPPG has the interes…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingLinear programming[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputer science0206 medical engineeringAutocorrelation[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Context (language use)02 engineering and technology[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]020601 biomedical engineering01 natural sciencesMulti-objective optimizationIndependent component analysis010309 optics[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing0103 physical sciencesA priori and a posterioriRGB color modelLinear combinationAlgorithm
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Detection and matching of curvilinear structures

2011

We propose an approach to curvilinear and wiry object detection and matching based on a new curvilinear region detector (CRD) and a shape context-like descriptor (COH). Standard methods for local patch detection and description are not directly applicable to wiry objects and curvilinear structures, such as roads, railroads and rivers in satellite and aerial images, vessels and veins in medical images, cables, poles and fences in urban scenes, stems and tree branches in natural images, since they assume the object is compact, i.e. that most elliptical patches around features cover only the object. However, wiry objects often have no flat parts and most neighborhoods include both foreground a…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingMatching (graph theory)Computer science[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technology01 natural sciences010309 optics[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingArtificial Intelligence0103 physical sciences0202 electrical engineering electronic engineering information engineeringSegmentationComputer visionComputingMilieux_MISCELLANEOUSCurvilinear coordinatesbusiness.industryObject (computer science)Object detectionTree (data structure)Signal ProcessingPattern recognition (psychology)020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionArtificial intelligenceScale (map)business[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingSoftware
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