Search results for "texture"

showing 10 items of 402 documents

An Image Segmentation Algorithm based on Community Detection

2016

International audience; With the recent advances in complex networks, image segmentation becomes one of the most appropriate application areas. In this context, we propose in this paper a new perspective of image segmentation by applying two efficient community detection algorithms. By considering regions as communities, these methods can give an over-segmented image that has many small regions. So, the proposed algorithms are improved to automatically merge those neighboring regions agglomerative to achieve the highest modularity/stability. To produce sizable regions and detect homogeneous communities, we use the combination of a feature based on the Histogram of Oriented Gradients of the …

[ INFO ] Computer Science [cs]Computer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScale-space segmentation02 engineering and technology[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Minimum spanning tree-based segmentationImage texture0202 electrical engineering electronic engineering information engineeringcommunity detection[INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO]Segmentation[INFO]Computer Science [cs][ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]modularityImage segmentationSegmentation-based object categorizationbusiness.industry[ INFO.INFO-RB ] Computer Science [cs]/Robotics [cs.RO]Pattern recognitionImage segmentationcomplex networksHistogram of oriented gradientsRegion growing020201 artificial intelligence & image processingArtificial intelligencebusiness
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Approche coopérative pour l'acquisition et l'observation de formes tridimensionnelles

2009

Technologic progres can reduce the barrier between real image and virtual image so far it is really difficult to recognize them. When virtual reality is well done, augmented reality, from virtual world to real world, is still developped. We want to project a virtual texture onto a 3D real object. By using cameras and projector, we estimate its real pose in the virtual reference by projecting a coded pattern to find points of correspondence between cameras and projector onto the textureless object, where common detector of points of correspondence are useless. We combine the calibration of the system and these points to estimate the 3D position of the object, and then register with a fine mo…

[ INFO.INFO-MO ] Computer Science [cs]/Modeling and Simulationprojective textureLumière structuréeStructured lightréalité augmentée[INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation3D reconstructionreconstruction 3Détalonnagecalibration[INFO.INFO-MO]Computer Science [cs]/Modeling and Simulationaugmented realityprojection de texture
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Image registration for quality assessment of projection displays

2014

International audience; In the full reference metric based image quality assessment of projection displays, it is critical to achieve accurate and fully automatic image registration between the captured projection and its reference image in order to establish a subpixel level mapping. The preservation of geometrical order as well as the intensity and chromaticity relationships between two consecutive pixels must be maximized. The existing camera based image registration methods do not meet this requirement well. In this paper, we propose a markerless and view independent method to use an un-calibrated camera to perform the task. The proposed method including three main components: feature e…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingImage qualitybusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage registrationKanade–Lucas–Tomasi feature trackerImage processingImage texture[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingComputer visionArtificial intelligenceProjection (set theory)businessImage restorationMathematicsFeature detection (computer vision)
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Manufactured object sub-segmentation based on reflection motion estimation

2015

International audience; In computer vision, reflection is a long-standing problem, it covers image textures, makes original color difficult to recognize, complicates the understanding of the scene. Most of the time, it is considered as “noise”. Many methods are proposed in order to reduce or delete the reflection effects in the image, but generally, the performances are not quite satisfactory. While instead of working on “de-noising”, we propose a method to take advantage of moving reflections that can be used for different computer vision applications. For instance, the segmentation of reflective manufactured objects is presented in this paper. We focus on tracking reflection components an…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingSegmentation-based object categorizationbusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScale-space segmentationPattern recognition02 engineering and technologyImage segmentation01 natural sciencesScale space010309 opticsImage texture[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingRegion growingMotion estimation0103 physical sciences0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingComputer visionArtificial intelligenceReflection (computer graphics)businessMathematics
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Roughness evaluation of vine leaf by image processing

2013

International audience; The study of leaf surface roughness is very important in the domain of precision spraying. It is one of the parameters that allow to reduce costs and losses of phytosanitary prod- ucts and to improve the spray accuracy. Moreover, the leaf roughness is related to adhesion mechanisms of liquid on a surface. It can be used to define leaf nature surface (hy- drophilic/hydrophobic). The main goal of this study is thus to estimate and to follow the evolution of leaf roughness using image processing and computer vision. The develop- ment and application of computer vision for measurement of surface leaf roughness using artificial neural networks will be described. The syste…

[ MATH ] Mathematics [math]0106 biological sciences0209 industrial biotechnologyScanning electron microscope[SDV]Life Sciences [q-bio]Computer Vision[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing[MATH] Mathematics [math]02 engineering and technologySurface finishLeaf roughness01 natural sciences[PHYS] Physics [physics][SPI]Engineering Sciences [physics]020901 industrial engineering & automation[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[ SPI ] Engineering Sciences [physics]Surface roughnessComputer vision[MATH]Mathematics [math]ComputingMilieux_MISCELLANEOUS[PHYS]Physics [physics][ PHYS ] Physics [physics]Artificial neural network[STAT]Statistics [stat]Multilayer perceptron[SDE]Environmental SciencesBiological system[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingMaterials science[ STAT ] Statistics [stat][INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing[SPI] Engineering Sciences [physics]IASTEDFast Fourier transformNeural NetworkImage processingImage processing[SDV.BV]Life Sciences [q-bio]/Vegetal BiologyTexturelanguage technologies[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingPrecision agriculturebusiness.industry[STAT] Statistics [stat]Precision agricultureArtificial intelligencebusiness010606 plant biology & botany
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Texture-aroma interactions in dairy products: Do in-vivo and in-vitro aroma release explain sensory perception?

2008

International audience; The influence of the texture on perceived aroma intensity and on in-vivo and in-vitro aroma release was investigated on three types of dairy products, prepared with different textures. Aroma release depends on in mouth breakdown of the product. The consequences of a textural modification on aroma perception were not the same for the different products. In the case of liquid to semi-liquid products (yogurt and custard dessert), in-vivo aroma release decreased when viscosity increased. For firm gels (model cheeses) in-vivo aroma release was found to increase when cheese hardness increased, but inverse results were obtained in in-vitro conditions. Thus, aroma release co…

[ SDV.AEN ] Life Sciences [q-bio]/Food and Nutrition[SDV.IDA]Life Sciences [q-bio]/Food engineeringin vivo and in vitro aroma releasefood and beveragesAPCI-MSaroma perception[SDV.AEN]Life Sciences [q-bio]/Food and NutritiontextureComputingMilieux_MISCELLANEOUS
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Modelling of interference fits with taking into account surfaces roughness with homogenization technique

2013

International audience; The assembly technique by shrink fit is increasingly used today because it allows for the assembly of two pieces without any intermediary part simply by the tightening effect given by the difference in diameters of the two parts assembled. The definition of assemblies depends on calculation models available in the standard. They make very restrictive assumptions that limit the geometrical defects and the surface finish. It is increasingly common to use a finite element method to better adapt the model to the complex forms of industrial parts. However, the standard is limited with regard to the consideration of roughness which results in a loss of tightening. An easy …

[ SPI.MECA.GEME ] Engineering Sciences [physics]/Mechanics [physics.med-ph]/Mechanical engineering [physics.class-ph]EngineeringRotational symmetry[PHYS.MECA.GEME]Physics [physics]/Mechanics [physics]/Mechanical engineering [physics.class-ph]02 engineering and technologySurface finishHomogenization (chemistry)[PHYS.MECA.MEMA]Physics [physics]/Mechanics [physics]/Mechanics of materials [physics.class-ph]0203 mechanical engineeringTransverse isotropy[SPI.MECA.MEMA]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Mechanics of materials [physics.class-ph]General Materials ScienceCivil and Structural Engineeringshrink fitbusiness.industryMechanical EngineeringMicroscopic levelhomogenization finite element techniqueMechanicsStructural engineering021001 nanoscience & nanotechnologyCondensed Matter PhysicsFinite element method[SPI.MECA.GEME]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Mechanical engineering [physics.class-ph]020303 mechanical engineering & transportsMechanics of Materials[ SPI.MECA.MEMA ] Engineering Sciences [physics]/Mechanics [physics.med-ph]/Mechanics of materials [physics.class-ph][ PHYS.MECA.MEMA ] Physics [physics]/Mechanics [physics]/Mechanics of materials [physics.class-ph][ PHYS.MECA.GEME ] Physics [physics]/Mechanics [physics]/Mechanical engineering [physics.class-ph]Micro-geometrical surface texture0210 nano-technologybusinessInterference fit
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Multi-Kernel Implicit Curve Evolution for Selected Texture Regions Segmentation in VHR Satellite Images

2014

Very high resolution (VHR) satellite images provide a mass of detailed information which can be used for urban planning, mapping, security issues, or environmental monitoring. Nevertheless, the processing of this kind of image is timeconsuming, and extracting the needed information from among the huge quantity of data is a real challenge. For some applications such as natural disaster prevention and monitoring (typhoon, flood, bushfire, etc.), the use of fast and effective processing methods is demanded. Furthermore, such methods should be selective in order to extract only the information required to allow an efficient interpretation. For this purpose, we propose a texture region segmentat…

[INFO.INFO-AR]Computer Science [cs]/Hardware Architecture [cs.AR][INFO.INFO-AR] Computer Science [cs]/Hardware Architecture [cs.AR]Pixelbusiness.industryComputer science0211 other engineering and technologiesGraphics processing unitBoundary (topology)Scale-space segmentation02 engineering and technologyImage segmentationFuzzy logicImage texture11. Sustainability0202 electrical engineering electronic engineering information engineeringGeneral Earth and Planetary Sciences020201 artificial intelligence & image processingComputer visionSegmentation[ INFO.INFO-AR ] Computer Science [cs]/Hardware Architecture [cs.AR]Artificial intelligenceElectrical and Electronic EngineeringbusinessComputingMilieux_MISCELLANEOUS021101 geological & geomatics engineering
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Détermination de la texture de la feuille de vigne par imagerie

2013

National audience; Dans le contexte de la pulvérisation de précision, nombreuses sont les recherches menées sur l'optimisation d'utilisation des produits phytosanitaires. L'objectif final étant de réduire de manière significative la quantité d'intrant dans les cultures . Dans ce cadre, les travaux présentés dans cet article s'intéresse particulièrement à l'analyse de l'état de surface foliaire qui présente une part essentielle dans le processus d'adhésion du produit pulvérisé sur la feuille. L'analyse de surface de la feuille est réalisée à travers l'analyse des caractéristiques texturale extraites d'images microscopics. Afin de discriminer les différents cépages et âges des feuilles retenu…

[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Analyse discriminante linéaire et non linéaire[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]TextureDescripteur Généralise de FourierRéseau de neuronessurface foliaire[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]
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Real-time implementation of counting people in a crowd on the embedded reconfigurable architecture on the unmanned aerial vehicle

2020

The crowd counting task is an important research problem. Now more and more people are concerned about safety issues. Considering the scenario of a crowded scene: a population density system analyzes the crowds and triggers a warning to divert the crowds when their population density exceeds a normal range. With such a system, the incident of the Shanghai New Year's stampede will not happen again. The most difficult problem of population counting at present: On the one hand, in the densely populated area, how to make the model distinguish human head features more finely, such as head overlap. The second aspect is to find a small-scale local head feature in an image with a wide range of popu…

[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV]M-Mcnn[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]Edge detectionDétection de contoursCaractéristiques de textureTexture featuresFpga
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