Search results for "ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION"

showing 10 items of 982 documents

HDR-­ARtiSt: a FPGA-­based Smart Camera for High Dynamic Range color video from multiple exposures

2014

International audience; A camera is able to capture only a part of a high dynamic range scene information. The same scene can be fully perceived by the human visual system. This is true especially for real scenes where the difference in light intensity between the dark areas and bright areas is high. The imaging technique which can overcome this problem is called HDR (High Dynamic Range). It produces images from a set of multiple LDR images (Low Dynamic Range), captured with different exposure times. This technique appears as one of the most appropriate and a cheap solution to enhance the dynamic range of captured environments. We developed an FPGA-based smart camera that produces a HDR liv…

parallel processingFPGA implementationComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONSmart cameraHigh dynamic rangeimage enhancement[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingimage reconstruction[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
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UNE APPROCHE PARALLELE D'EVALUATION DES PARAMETRES DE TEXTURE POUR L'ANALYSE D'IMAGES DE GRANDE TAILLE

2011

International audience; The main objective of this paper is to develop a new image processing technique that could better be adapted to the processing of large and complex images, especially SAR images, in relation to the former methods of our works. We propose here a new approach of textural parameters evaluation which is about (Ng+1)n-1 times faster than the co-occurrence matrix approach considered as classical, where n is the order of the textural parameter and Ng being the maximum grey level in the image. This approach is based on a new modeling of textural parameters of a generic order n>1 equivalent to the classical formulation, but which is no longer based on frequency matrix (co-occ…

parallelism[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV]image analysis[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV][ INFO.INFO-TI ] Computer Science [cs]/Image ProcessingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONtextural parametersmodelingtexture
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Visual saliency by keypoints distribution analysis

2011

In this paper we introduce a new method for Visual Saliency detection. The goal of our method is to emphasize regions that show rare visual aspects in comparison with those showing frequent ones. We propose a bottom up approach that performs a new technique based on low level image features (texture) analysis. More precisely, we use SIFT Density Maps (SDM), to study the distribution of keypoints into the image with different scales of observation, and its relationship with real fixation points. The hypothesis is that the image regions that show a larger distance from the mode (most frequent value) of the keypoints distribution over all the image are the same that better capture our visual a…

saliency visual attentiontexture SIFTComputer sciencebusiness.industryFixation (visual)ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONVisual attentionScale-invariant feature transformPattern recognitionComputer visionTop-down and bottom-up designArtificial intelligencebusinessVisual saliency
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Automated Detection of Microaneurysms Using Scale-Adapted Blob Analysis and Semi-Supervised Learning

2014

International audience; Despite several attempts, automated detection of microaneurysm (MA) from digital fundus images still remains to be an open issue. This is due to the subtle nature of MAs against the surrounding tissues. In this paper, the microaneurysm detection problem is modeled as finding interest regions or blobs from an image and an automatic local-scale selection technique is presented. Several scale-adapted region descriptors are then introduced to characterize these blob regions. A semi-supervised based learning approach, which requires few manually annotated learning examples, is also proposed to train a classifier to detect true MAs. The developed system is built using only…

semi-supervised learningFundus OculiComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONMicroaneurysmsblobsHealth Informatics02 engineering and technologySemi-supervised learningFundus (eye)[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]030218 nuclear medicine & medical imagingScale spaceAutomation03 medical and health scienceschemistry.chemical_compound0302 clinical medicine0202 electrical engineering electronic engineering information engineeringmedicineHumansLearningComputer visionBlob analysisMicroaneurysmbusiness.industry[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]RetinalDiabetic retinopathymedicine.diseaseAneurysmComputer Science Applicationsdiabetic retinopathyfundus imagechemistryscale-space.scale-space020201 artificial intelligence & image processingArtificial intelligencebusinessClassifier (UML)SoftwareRetinopathy
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A Multi-Projector Calibration Method for Virtual Reality Simulators with Analytically Defined Screens

2017

The geometric calibration of projectors is a demanding task, particularly for the industry of virtual reality simulators. Different methods have been developed during the last decades to retrieve the intrinsic and extrinsic parameters of projectors, most of them being based on planar homographies and some requiring an extended calibration process. The aim of our research work is to design a fast and user-friendly method to provide multi-projector calibration on analytically defined screens, where a sample is shown for a virtual reality Formula 1 simulator that has a cylindrical screen. The proposed method results from the combination of surveying, photogrammetry and image processing approac…

simulatorComputer scienceCalibration (statistics)ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processing02 engineering and technologyVirtual realitylcsh:Computer applications to medicine. Medical informatics01 natural scienceslcsh:QA75.5-76.95010309 opticsSimulació per ordinadorComputer graphics (images)0103 physical sciences0202 electrical engineering electronic engineering information engineeringimage processing; projector calibration; virtual reality; simulator; surveyingRadiology Nuclear Medicine and imagingPoint (geometry)lcsh:PhotographysurveyingElectrical and Electronic EngineeringRealitat virtualProcess (computing)020207 software engineeringlcsh:TR1-1050Computer Graphics and Computer-Aided DesignSample (graphics)projector calibrationimage processingTask (computing)Photogrammetryvirtual realitylcsh:R858-859.7lcsh:Electronic computers. Computer scienceComputer Vision and Pattern RecognitionImatges ProcessamentJournal of Imaging
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Video Scene analysis for a configurable hardware accelerator dedicated to Smart Camera

2012

International audience; According to the Center for Research and Prevention of Injuries report, fall-caused injuries of elderly people in UE- 27 are five times as frequent as other injury causes which reduce considerably their mobility and independence. Among the diverse applications of computer vision systems, object detection and event recognition are of the most prominent related recognition and motion analysis, that is, researchers had the idea to spread it in fall detection. The fall event, extracted automatically from the video scene represents itself, crucial information that can be used to alert emergency. In this context, visual information on the corresponding scene is highly impo…

smart camera's acceleratorConfigurable motion estimationadaptive video coding performancesFall detectionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION[INFO.INFO-ES]Computer Science [cs]/Embedded Systems[ INFO.INFO-ES ] Computer Science [cs]/Embedded Systems[INFO.INFO-ES] Computer Science [cs]/Embedded Systems
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Multispectral filter arrays: Recent advances and practical implementation

2014

Thanks to some technical progress in interferencefilter design based on different technologies, we can finally successfully implement the concept of multispectral filter array-based sensors. This article provides the relevant state-of-the-art for multispectral imaging systems and presents the characteristics of the elements of our multispectral sensor as a case study. The spectral characteristics are based on two different spatial arrangements that distribute eight different bandpass filters in the visible and near-infrared area of the spectrum. We demonstrate that the system is viable and evaluate its performance through sensor spectral simulation. Multispectral filter arrays: Recent advan…

snapshotmultispectral imaging[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer scienceMultispectral imageComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technologylcsh:Chemical technologycomputer.software_genre01 natural sciencesBiochemistryArticleAnalytical Chemistry010309 opticsBand-pass filter[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing0103 physical sciencesElectronic engineeringlcsh:TP1-1185Electrical and Electronic EngineeringInstrumentationsnapshot multispectral imaging021001 nanoscience & nanotechnologyAtomic and Molecular Physics and Opticssingle solid state sensorspatio-spectral scene samplingComputingMethodologies_PATTERNRECOGNITIONFilter (video)multispectral and color filter arraysData mining0210 nano-technologycomputer
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The Radon-Wigner Transform and Its Application to First-order Optical Systems

2009

The Radon-Wigner transform is presented as a tool for the description of 1st-order optical systems. The input/output relationships for this phase-space representation are obtained and their application in analysis and design tasks is pointed out.

symbols.namesakeFourier transformComputer scienceHartley transformComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONsymbolsShort-time Fourier transformHarmonic wavelet transformS transformAlgorithmConstant Q transformDiscrete Fourier transformFractional Fourier transformFrontiers in Optics 2009/Laser Science XXV/Fall 2009 OSA Optics & Photonics Technical Digest
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Interface Detection Using a Quenched-Noise Version of the Edwards-Wilkinson Equation

2015

We report here a multipurpose dynamic-interface-based segmentation tool, suitable for segmenting planar, cylindrical, and spherical surfaces in 3D. The method is fast enough to be used conveniently even for large images. Its implementation is straightforward and can be easily realized in many environments. Its memory consumption is low, and the set of parameters is small and easy to understand. The method is based on the Edwards-Wilkinson equation, which is traditionally used to model the equilibrium fluctuations of a propagating interface under the influence of temporally and spatially varying noise. We report here an adaptation of this equation into multidimensional image segmentation, an…

ta113Image segmentationta114DiscretizationInterface (Java)Computer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONobject detectionimage edge detectionImage segmentationComputer Graphics and Computer-Aided DesignGrayscaleGray-scaleObject detectionSurface topographyNoiseMathematical modelThree-dimensional displaysSegmentationTomography3D image processingNoiseSurface morphologyAlgorithmSoftwareIEEE Transactions on Image Processing
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Automatic dynamic texture segmentation using local descriptors and optical flow

2012

A dynamic texture (DT) is an extension of the texture to the temporal domain. How to segment a DT is a challenging problem. In this paper, we address the problem of segmenting a DT into disjoint regions. A DT might be different from its spatial mode (i.e., appearance) and/or temporal mode (i.e., motion field). To this end, we develop a framework based on the appearance and motion modes. For the appearance mode, we use a new local spatial texture descriptor to describe the spatial mode of the DT; for the motion mode, we use the optical flow and the local temporal texture descriptor to represent the temporal variations of the DT. In addition, for the optical flow, we use the histogram of orie…

ta113business.industrySegmentation-based object categorizationComputer scienceTexture DescriptorComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONOptical flowScale-space segmentationPattern recognitionImage segmentationComputer Graphics and Computer-Aided DesignImage textureMotion fieldRegion growingComputer Science::Computer Vision and Pattern RecognitionHistogramComputer visionSegmentationArtificial intelligencebusinessSoftwareIEEE Transactions on Image Processing
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