Search results for "ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION"

showing 10 items of 982 documents

Distance-based functions for image comparison

1999

The interest in digital image comparison is steadily growing in the computer vision community. The definition of a suitable comparison measure for non-binary images is relevant in many image processing applications. Visual tasks like segmentation and classification require the evaluation of equivalence classes. Measures of similarity are also used to evaluate lossy compression algorithms and to define pictorial indices in image content based retrieval methods. In this paper we develop a distance-based approach to image similarity evaluation and we present several image distances which are based on low level features. The sensitivity and eAectiveness are tested on real data. ” 1999 Published…

Standard test imagebusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processingPattern recognitionImage segmentationAutomatic image annotationImage textureArtificial IntelligenceSignal ProcessingDigital image processingComputer visionComputer Vision and Pattern RecognitionArtificial intelligencebusinessImage retrievalSoftwareMathematicsFeature detection (computer vision)Pattern Recognition Letters
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Spatio‐temporal classification in point patterns under the presence of clutter

2019

We consider the problem of detection of features in the presence of clutter for spatio-temporal point patterns. In previous studies, related to the spatial context, Kth nearest-neighbor distances to classify points between clutter and features. In particular, a mixture of distributions whose parameters were estimated using an expectation-maximization algorithm. This paper extends this methodology to the spatio-temporal context by considering the properties of the spatio-temporal Kth nearest-neighbor distances. For this purpose, we make use of a couple of spatio-temporal distances, which are based on the Euclidean and the maximum norms. We show close forms for the probability distributions o…

Statistics and Probability010504 meteorology & atmospheric sciencesComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONContext (language use)01 natural sciences010104 statistics & probabilitySpatio-temporalpoint patternsClutterExpectation–maximization algorithmEuclidean geometryEarthquakesPoint (geometry)clutter earthquakes EM algorithm features mixtures nearest‐neighbor distances spatio‐temporal point patterns0101 mathematicsEM algorithmFeatures0105 earth and related environmental sciencesspatio-temporal point patternSpatial contextual awarenessEcological Modelingmixturenearest-neighbor distanceComputingMethodologies_PATTERNRECOGNITIONearthquakeMixturesProbability distributionClutterfeatureSettore SECS-S/01 - StatisticaclutterNearest-neighbor distancesAlgorithmEnvironmetrics
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What we look at in paintings: A comparison between experienced and inexperienced art viewers

2016

How do people look at art? Are there any differences between how experienced and inexperienced art viewers look at a painting? We approach these questions by analyzing and modeling eye movement data from a cognitive art research experiment, where the eye movements of twenty test subjects, ten experienced and ten inexperienced art viewers, were recorded while they were looking at paintings. Eye movements consist of stops of the gaze as well as jumps between the stops. Hence, the observed gaze stop locations can be thought as a spatial point pattern, which can be modeled by a spatio-temporal point process. We introduce some statistical tools to analyze the spatio-temporal eye movement data, a…

Statistics and ProbabilityFOS: Computer and information sciencesCoverageComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION01 natural sciencesStatistics - Applications050105 experimental psychologyVisual arts010104 statistics & probabilitysilmänliikkeetInformationSystems_MODELSANDPRINCIPLES0501 psychology and cognitive sciencesApplications (stat.AP)0101 mathematicspoint processPaintingPoint (typography)05 social sciencesEye movementCognitioncognitive art researchtransition probabilityGazeTest (assessment)shift functionModeling and Simulationart viewersStatistics Probability and UncertaintyPsychologyintensity
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A new method for linear affine self-calibration of stationary zooming stereo cameras

2012

This paper presents a simple, yet effective, method to recover the affine structure of a scene from a (stereo) pair of stationary zooming cameras. The proposed method solely relies on point correspondences across images and no knowledge about the scene whatsoever is required. Our method exploits implicit properties of the projective camera matrices of zooming cameras and allows to estimate the affine structure of a scene by solving a linear system of equations. The 3D reconstruction results obtained by using our method, on both real and simulated data, have remarkably validated its feasibility.

Stereo camerasbusiness.industry3D reconstructionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONIterative reconstructionAffine shape adaptationComputer Science::GraphicsComputer Science::Computer Vision and Pattern RecognitionLinear algebraComputer visionAffine transformationArtificial intelligenceZoombusinessStereo cameraComputingMethodologies_COMPUTERGRAPHICSMathematics2012 19th IEEE International Conference on Image Processing
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3-D shape reconstruction in an active stereo vision system using genetic algorithms

2003

Abstract The recovery of 3-D shape information (depth) using stereo vision analysis is one of the major areas in computer vision and has given rise to a great deal of literature in the recent past. The widely known stereo vision methods are the passive stereo vision approaches that use two cameras. Obtaining 3-D information involves the identification of the corresponding 2-D points between left and right images. Most existing methods tackle this matching task from singular points, i.e. finding points in both image planes with more or less the same neighborhood characteristics. One key problem we have to solve is that we are on the first instance unable to know a priori whether a point in t…

Stereo camerasbusiness.industryComputer scienceMachine visionEpipolar geometry3D reconstructionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONlaw.inventionStereopsisProjectorArtificial IntelligencelawSignal ProcessingComputer visionComputer Vision and Pattern RecognitionArtificial intelligenceFundamental matrix (computer vision)businessSoftwareComputer stereo visionStereo cameraPattern Recognition
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Structure from motion using a hybrid stereo-vision system

2015

International audience; This paper is dedicated to robotic navigation using an original hybrid-vision setup combining the advantages offered by two different types of camera. This couple of cameras is composed of one perspective camera associated with one fisheye camera. This kind of configuration , is also known under the name of foveated vision system since it is inspired by the human vision system and allows both a wide field of view and a detail front view of the scene. Here, we propose a generic and robust approach for SFM, which is compatible with a very broad spectrum of multi-camera vision systems, suitable for perspective and om-nidirectional cameras, with or without overlapping fi…

Stereo camerasbusiness.industryComputer scienceMachine vision[ INFO.INFO-RB ] Computer Science [cs]/Robotics [cs.RO][INFO.INFO-RB] Computer Science [cs]/Robotics [cs.RO]ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONField of viewStereopsisComputer graphics (images)Structure from motion[INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO]Computer visionSmart cameraArtificial intelligencebusinessComputer stereo visionStereo camera
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A tool for a first analysis of architectural façades

1997

Abstract This work presents a tool for analysing the figurative structure of architectural facades. The procedure begins by singling out the elementary shapes which make up the facade image; it detects and identifies them as “area objects”, even if present in combination in virtual or mental form and groups them into classes of equal objects. A second step is the analysis of the inner structure of the classes: equidistant, arithmetical and geometrical sequences, or alternate distances are distinguished. The procedure ends by singling out the symmetries which structure the facade image and displaying them, pointing out their implied hierarchy through a thickness differentiation.

Structure (mathematical logic)Engineering drawingEngineeringHierarchy (mathematics)business.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONBuilding and ConstructionImage (mathematics)Facade patternControl and Systems EngineeringHomogeneous spaceArithmetic functionEquidistantFacadebusinessCivil and Structural EngineeringAutomation in Construction
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A deep semantic segmentation-based algorithm to segment crops and weeds in agronomic color images

2022

Abstract In precision agriculture, the accurate segmentation of crops and weeds in agronomic images has always been the center of attention. Many methods have been proposed but still the clean and sharp segmentation of crops and weeds is a challenging issue for the images with a high presence of weeds. This work proposes a segmentation method based on the combination of semantic segmentation and K-means algorithms for the segmentation of crops and weeds in color images. Agronomic images of two different databases were used for the segmentation algorithms. Using the thresholding technique, everything except plants was removed from the images. Afterward, semantic segmentation was applied usin…

Subtractive colorComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONConfusion matrixForestryAquatic ScienceThresholdingAccurate segmentationComputer Science ApplicationsClassification rateAnimal Science and ZoologySegmentationPrecision agricultureCluster analysisAgronomy and Crop ScienceAlgorithmInformation Processing in Agriculture
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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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HD-RTI: an adaptive multi-light imaging approach for the quality assessment of manufactured surfaces

2021

International audience; Reflectance Transformation Imaging (RTI) is a technique for estimating surface local angular reflectance from a set of stereo-photometric images captured with variable lighting directions. The digitization of this information fully fits into the industry 4.0 approach and makes it possible to characterize the visual properties of a surface. The proposed method, namely HD-RTI, is based on the coupling of RTI and HDR imaging techniques. This coupling is carried out adaptively according to the response at each angle of illumination. The proposed method is applied to five industrial samples which have high local variations of reflectivity because of their heterogeneity of…

Surface (mathematics)0209 industrial biotechnologyGeneral Computer ScienceComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technologyMachine visionSet (abstract data type)020901 industrial engineering & automationQuality (physics)[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingRobustness (computer science)0202 electrical engineering electronic engineering information engineeringComputer visionComputingMethodologies_COMPUTERGRAPHICSCouplingbusiness.industryQuality assessmentGeneral Engineering[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Variable (computer science)Quality inspection020201 artificial intelligence & image processingArtificial intelligenceMaterial AppearancebusinessPolynomial texture mapping
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