Search results for "Computer Vision and Pattern Recognition"

showing 10 items of 997 documents

Modular Method of Detection, Localization and Counting of Mutliple-Taxon Pollen Apertures Using Bag of Words

2014

International audience; Accurate recognition of airborne pollen taxa is crucial for understanding and treating allergic diseases, which affect an important proportion of the world population. Modern computer vision techniques enables the detection of discriminant characteristics. Apertures is one of these characteristic that has been little explored up to now. In this paper, a flexible method of detection, localization and counting of apertures of different pollen taxa with varying appearances is proposed. Apertures are described based by primitive images following the Bag-of-Words strat-egy. A confidence map is estimated based on the classification of sampled regions. The method is designe…

Contextual image classificationComputer sciencebusiness.industryLocal binary patternspattern recognitionaperturesCognitive neuroscience of visual object recognition[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Image segmentationmedicine.disease_cause[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Atomic and Molecular Physics and OpticsComputer Science Applicationsbag of wordsRobustness (computer science)Bag-of-words modelPollenLBPPattern recognition (psychology)medicineComputer visionArtificial intelligenceElectrical and Electronic Engineeringbusinesspalynology
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A note on the iterative object symmetry transform

2004

This paper introduces a new operator named the iterated object transform that is computed by combining the object symmetry transform with the morphological operator erosion. This new operator has been applied on both binary and gray levels images showing the ability to grasp the internal structure of a digital object. We present also some experiments on artificial and real images and potential applications.

Contextual image classificationbusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONTop-hat transformMathematical morphologyErosion (morphology)Object (computer science)Real imageOperator (computer programming)Artificial IntelligenceSignal ProcessingComputer visionComputer Vision and Pattern RecognitionArtificial intelligenceSymmetry (geometry)businessSoftwareMathematicsPattern Recognition Letters
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Reliable Planar Object Pose Estimation in Light Fields From Best Subaperture Camera Pairs

2018

International audience; A light-field camera can obtain richer information about a scene than a usual camera. This property offers a lot of potential for robot vision. In this paper, we present a method for pose estimation of a planar object with a light-field camera. The light-field camera can be regarded as a set of sub-aperture cameras. Although any combination of them can theoretically be used for the pose estimation, the accuracy depends on the combination. We show that the estimated pose error can be reduced by selecting the best pair of sub-aperture cameras. We have evaluated the accuracy of our approach with real experiments using a light-field camera in front of planar targets held…

Control and OptimizationComputer scienceProperty (programming)Biomedical EngineeringComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONSet (abstract data type)PlanarArtificial Intelligence[INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO]Computer visionPoseComputer Science::DatabasesGround truthbusiness.industryMechanical EngineeringAstrophysics::Instrumentation and Methods for Astrophysics[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]16. Peace & justiceObject (computer science)Computer Science ApplicationsHuman-Computer InteractionControl and Systems EngineeringComputer Science::Computer Vision and Pattern RecognitionComputer Vision and Pattern RecognitionArtificial intelligencebusiness
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Experiments with an adaptive Bayesian restoration method

1989

Abstract This paper describes a Bayesian restoration method applied to two-dimensional measured images, whose detector response function is not completely known. The response function is assumed Gaussian with standard deviation depending on the estimate of the local density of the image. The convex hull of the K -nearest neighbours ( K NN) of each ‘on’ pixel is used to compute the local density. The method has been tested on ‘sparse’ images, with and without noise background.

Convex hullGaussianImage processingStandard deviationsymbols.namesakeArtificial IntelligenceBayesian restorationElectrical and Electronic EngineeringImage restorationK-nearest-neighbours algorithmMathematics1707PixelSettore INF/01 - Informaticabusiness.industryPattern recognitionsparse imageFunction (mathematics)Signal ProcessingsymbolsComputer Vision and Pattern RecognitionArtificial intelligenceDeconvolutionbusinessconvex hullSoftware
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Graph cut-based method for segmenting the left ventricle from MRI or echocardiographic images

2017

International audience; In this paper, we present a fast and interactive graph cut method for 3D segmentation of the endocardial wall of the left ventricle (LV) adapted to work on two of the most widely used modalities: magnetic resonance imaging (MRI) and echocardiography. Our method accounts for the fundamentally different nature of both modalities: 3D echocardiographic images have a low contrast, a poor signal-to-noise ratio and frequent signal drop, while MR images are more detailed but also cluttered and contain highly anisotropic voxels. The main characteristic of our method is to work in a 3D Bezier coordinate system instead of the original Euclidean space. This comes with several ad…

Convex hullHeart VentriclesEnergy MinimizationCoordinate systemEchocardiography Three-DimensionalHealth InformaticsBézier curve02 engineering and technology[SDV.IB.MN]Life Sciences [q-bio]/Bioengineering/Nuclear medicinecomputer.software_genreAutomated Segmentation030218 nuclear medicine & medical imaging[ SDV.IB.MN ] Life Sciences [q-bio]/Bioengineering/Nuclear medicine03 medical and health sciences0302 clinical medicineVoxelCut0202 electrical engineering electronic engineering information engineering[INFO.INFO-IM]Computer Science [cs]/Medical ImagingMagnetic-Resonance ImagesHumansRadiology Nuclear Medicine and imagingComputer vision[ SDV.IB ] Life Sciences [q-bio]/BioengineeringCardiac MriImage gradientMathematicsWhole MyocardiumLeft ventricular 3-D segmentationRadiological and Ultrasound Technology[ INFO.INFO-IM ] Computer Science [cs]/Medical ImagingEuclidean spacebusiness.industryComputer Graphics and Computer-Aided DesignMagnetic Resonance ImagingEchocardiographyConstrained Level-SetGraph (abstract data type)020201 artificial intelligence & image processing[SDV.IB]Life Sciences [q-bio]/BioengineeringComputer Vision and Pattern RecognitionArtificial intelligencebusiness2d-EchocardiographycomputerAlgorithmsGraph cutMRI
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Shape-Based Features for Cat Ganglion Retinal Cells Classification

2002

This article presents a quantitative and objective approach to cat ganglion cell characterization and classification. The combination of several biologically relevant features such as diameter, eccentricity, fractal dimension, influence histogram, influence area, convex hull area, and convex hull diameter are derived from geometrical transforms and then processed by three different clustering methods (Ward’s hierarchical scheme, K-means and genetic algorithm), whose results are then combined by a voting strategy. These experiments indicate the superiority of some features and also suggest some possible biological implications.

Convex hullSettore INF/01 - InformaticaComputer sciencebusiness.industryFeature extractionPattern recognitionComputational geometryFractal dimensionbody regionsFractalHistogramSignal ProcessingGenetic algorithmComputer visionMedical imagingComputer Vision and Pattern RecognitionArtificial intelligenceElectrical and Electronic EngineeringCells classificationCluster analysisbusinessReal-Time Imaging
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Stabilization and lx -gain analysis of switched positive systems with actuator saturation

2014

This paper is concerned with the problems of stability and l 1 -gain analysis for a class of switched positive systems with time-varying delays and actuator saturation. Firstly, a convex hull representation is used to describe the saturation behavior. By constructing a multiple co-positive Lyapunov functional, sufficient conditions are provided for the closed-loop system to be locally asymptotically stable at the origin of the state space under arbitrary switching. Then, the l 1 -gain performance analysis in the presence of actuator saturation is developed. Finally, two numerical examples are provided to demonstrate the effectiveness of the proposed method.

Convex hulll<inf>1</inf>-gain performanceApplied MathematicsTime-varying delaysActuator saturationComputer Science Applications1707 Computer Vision and Pattern RecognitionPositive systemsActuator saturation; l<inf>1</inf>-gain performance; Positive systems; Switched systems; Time-varying delays; Computer Science Applications1707 Computer Vision and Pattern Recognition; Control and Systems Engineering; Applied Mathematics; Modeling and SimulationStability (probability)Positive systemsActuator saturationControl theoryControl and Systems EngineeringStability theoryModeling and SimulationState spaceRepresentation (mathematics)Saturation (chemistry)Switched systemsMathematics
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Mammographic images segmentation based on chaotic map clustering algorithm

2013

Background: This work investigates the applicability of a novel clustering approach to the segmentation of mammographic digital images. The chaotic map clustering algorithm is used to group together similar subsets of image pixels resulting in a medically meaningful partition of the mammography. Methods: The image is divided into pixels subsets characterized by a set of conveniently chosen features and each of the corresponding points in the feature space is associated to a map. A mutual coupling strength between the maps depending on the associated distance between feature space points is subsequently introduced. On the system of maps, the simulated evolution through chaotic dynamics leads…

Cooperative behaviorClustering algorithmsComputer scienceFeature vectorCorrelation clusteringPhysics::Medical PhysicsMass lesionsMicrocalcificationsImage processingBreast NeoplasmsDigital imageSegmentationBreast cancerImage Processing Computer-AssistedCluster AnalysisHumansRadiology Nuclear Medicine and imagingSegmentationComputer visionCluster analysisFeaturesPixelChaotic maps Clustering algorithms Cooperative behavior Segmentation Mammography Features Mass lesions Microcalcifications Breast cancerbusiness.industrySegmentation-based object categorizationCalcinosisSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Radiographic Image EnhancementChaotic mapsRadiology Nuclear Medicine and imagingComputer Science::Computer Vision and Pattern RecognitionFemaleArtificial intelligencebusinessAlgorithmsMammographyResearch Article
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Granulometric moments and corneal endothelium status

2001

Abstract Specular microscopy is a common practice in Ophthalmology. The corneal endothelium status is usually evaluated by means of the density, the hexagonality, the mean, the standard deviation and the coefficient of variation of cell areas. We propose to replace the cell area moments by the corresponding moments of a different probability distribution, the granulometric size distribution associated to a disc. All cells touching the frame are ignored by the area moments but used by the granulometric moments. Twenty images have been analyzed. When the size of the focused region is reduced, the area moments show a greater variation than the corresponding granulometric moments.

Corneal endotheliumArtificial IntelligenceCoefficient of variationSignal ProcessingMathematical analysisSPECULAR MICROSCOPYStatisticsProbability distributionComputer Vision and Pattern RecognitionSoftwareStandard deviationShape analysis (digital geometry)MathematicsPattern Recognition
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MORPHOMETRIC ANALYSIS OF HUMAN CORNEAL ENDOTHELIUM BY MEANS OF SPATIAL POINT PATTERNS

2002

This paper presents a method for detecting abnormalities in spatial arrangements of cells within any tissue that can be described by different sets of relevant points. The method has been applied to the detection of subtle abnormalities in corneal endothelia. Images of this type of tissue can be characterized by two types of points: cell centroids and triple points associated with the apical intersections as it was proposed by Díaz.7 Both types of points jointly considered are modeled using a bivariate spatial point process; then a statistical analysis based on certain distributional descriptors proposed by Doguwa4,9 is carried out to discriminate severe and subtle abnormalities from contr…

Corneal endotheliumbusiness.industryCentroidPattern recognitionBivariate analysisPoint processMorphometric analysisArtificial IntelligenceCell densityStatisticsPoint (geometry)Statistical analysisComputer Vision and Pattern RecognitionArtificial intelligencebusinessSoftwareMathematicsInternational Journal of Pattern Recognition and Artificial Intelligence
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