Search results for "Sensor"

showing 10 items of 4594 documents

Self-Cleaning Bending Sensors Based on Semitransparent ZnO Nanostructured Films

2023

The design of multifunctional nanostructured materials is the key to the development of smart wearable devices. For instance, nanostructures endowed with both piezoelectric and photocatalytic activities could well be the workhorse for solar-light-driven self-cleaning wearable sensors. In this work, a simple strategy for the assembly of a flexible, semitransparent piezophotocatalytic system is demonstrated by leveraging rational wet chemistry synthesis of ZnO-based nanosheets/nanoflowers (NSs/NFs) under basic pH conditions onto flexible ITO/PET supports. A KMnO4 pretreatment before the ZnO synthesis (seeded ZnO) allows for the control of the density, size, and orientation of the NSs/NFs syst…

ZnO nanostructures piezotronics photocatalysis flexible sensors wearable deviceSettore CHIM/01 - Chimica AnaliticaSettore CHIM/02 - Chimica FisicaACS Applied Engineering Materials
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A Review on Applications of Big Data for Disaster Management

2017

International audience; The term " disaster management " comprises both natural and man-made disasters. Highly pervaded with various types of sensors, our environment generates large amounts of data. Thus, big data applications in the field of disaster management should adopt a modular view, going from a component to nation scale. Current research trends mainly aim at integrating component, building, neighborhood and city levels, neglecting the region level for managing disasters. Current research on big data mainly address smart buildings and smart grids, notably in the following areas: energy waste management, prediction and planning of power generation needs, improved comfort, usability …

[ INFO ] Computer Science [cs]Computer scienceBig data02 engineering and technology[INFO] Computer Science [cs]7. Clean energydisasters12. Responsible consumptionbig data020204 information systemsComponent (UML)11. Sustainability0202 electrical engineering electronic engineering information engineering[INFO]Computer Science [cs]Building automationEmergency managementbusiness.industry020207 software engineeringUsabilityEnergy consumptionDisaster managementsensor dataSystematic reviewSmart gridRisk analysis (engineering)13. Climate actionbusiness
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Maximum likelihood difference scaling of image quality in compression-degraded images.

2007

International audience; Lossy image compression techniques allow arbitrarily high compression rates but at the price of poor image quality. We applied maximum likelihood difference scaling to evaluate image quality of nine images, each compressed via vector quantization to ten different levels, within two different color spaces, RGB and CIE 1976 L(*)a(*)b(*). In L(*)a(*)b(*) space, images could be compressed on average by 32% more than in RGB space, with little additional loss in quality. Further compression led to marked perceptual changes. Our approach permits a rapid, direct measurement of the consequences of image compression for human observers.

[ INFO ] Computer Science [cs]Image qualityColorImage processing[INFO] Computer Science [cs]Color space050105 experimental psychology03 medical and health sciences0302 clinical medicineOpticsImage Processing Computer-Assisted[INFO]Computer Science [cs]0501 psychology and cognitive sciences[SDV.MHEP.OS]Life Sciences [q-bio]/Human health and pathology/Sensory OrgansImage resolutionMathematicsColor imagebusiness.industry05 social sciencesVector quantizationData CompressionAtomic and Molecular Physics and OpticsElectronic Optical and Magnetic Materials[SDV.MHEP.OS] Life Sciences [q-bio]/Human health and pathology/Sensory Organs[ SDV.MHEP.OS ] Life Sciences [q-bio]/Human health and pathology/Sensory OrgansRGB color modelComputer Vision and Pattern RecognitionArtifactsbusiness030217 neurology & neurosurgeryImage compression
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Needle-shape quality control by shadowgraphic image processing

2011

International audience; We propose a needle-shape quality-control method. To this end, we have devised a new acquisition system that combines a camera and a backlight. Needle measurements are carried out at a micrometric scale using shadowgraphic image processing. Our method not only distinguishes good needles from bad ones, but also allows classifying flawed needles into various categories of defects. This classification is important because some categories of defects can affect the entire production, whereas others do not. The results of our needle-shape quality-control method are validated using real samples directly off the manufacturing line. Needles are correctly classified at >97%, a…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer scienceImage qualityImage processing[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technologyBacklightMathematical morphology[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processingneedle020204 information systems[ INFO.INFO-TI ] Computer Science [cs]/Image Processing0202 electrical engineering electronic engineering information engineeringComputer visionquality controlImage sensorRadon transformbusiness.industryGeneral EngineeringImage segmentationAtomic and Molecular Physics and Opticsimage processingmetrology[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]020201 artificial intelligence & image processingArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingShape analysis (digital geometry)Optical Engineering
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A 1.3 megapixel FPGA-based smart camera for high dynamic range real time video

2013

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…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer science[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONVideo camera02 engineering and technologyTone mapping[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processinglaw.invention[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processinglaw0202 electrical engineering electronic engineering information engineeringComputer visionSmart cameraHigh dynamic range[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingCMOS sensorbusiness.industry020206 networking & telecommunicationsFrame rateLight intensityHuman visual system model020201 artificial intelligence & image processingArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Integration of 3D and multispectral data for cultural heritage applications: Survey and perspectives

2013

International audience; Cultural heritage is increasingly put through imaging systems such as multispectral cameras and 3D scanners. Though these acquisition systems are often used independently, they collect complementary information (spectral vs. spatial) used for the study, archiving and visualization of cultural heritage. Recording 3D and multispectral data in a single coordinate system enhances the potential insights in data analysis. Wepresent the state of the art of such acquisition systems and their applications for the study of cultural her- itage. Wealso describe existing registration techniques that can be used to obtain 3D models with multispec- tral texture and explore the idea…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingRegistration[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputer scienceMultispectral imageComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION3d model[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technologycomputer.software_genre3D digitizationMultispectral imaging[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing11. Sustainability0202 electrical engineering electronic engineering information engineering[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingMultispectral dataMultimedia020207 software engineeringData fusionSensor fusionData scienceVisualizationCultural heritagePhotogrammetryPhotogrammetrySignal ProcessingCultural heritage020201 artificial intelligence & image processingComputer Vision and Pattern Recognition[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingcomputerImage and Vision Computing
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Smart camera design for realtime High Dynamic Range imaging

2011

International audience; Many camera sensors suffer from limited dynamic range. The result is that there is a lack of clear details in displayed images and videos. This paper describes our approach to generate high dynamic range (HDR) from an image sequence while modifying exposure times for each new frame. For this purpose, we propose an FPGA-based architecture that can produce a real-time high dynamic range video from successive image acquisition. Our hardware platform is build around a standard low dynamic range CMOS sensor and a Virtex 5 FPGA board. The CMOS sensor is a EV76C560 provided by e2v. This 1.3 Megapixel device offers novel pixel integration/readout modes and embedded image pre…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingACM IEEEImagingVideosHardware[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingHigh-dynamic-range imaging0202 electrical engineering electronic engineering information engineeringComputer visionSmart cameraImage sensorImage resolutionHigh dynamic range[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingPipelinesCMOS sensorDynamic rangePixelbusiness.industrySensors020208 electrical & electronic engineeringReal time systems020207 software engineeringFrame rate[SPI.TRON]Engineering Sciences [physics]/Electronics[ SPI.TRON ] Engineering Sciences [physics]/ElectronicsArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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HDR-ARtiSt: High Dynamic Range Advanced Real-Time Imaging System

2012

International audience; This paper describes the HDR-ARtiSt hardware platform, a FPGA-based architecture that can produce a real- time high dynamic range video from successive image acquisition. The hardware platform is built around a standard low dynamic range (LDR) CMOS sensor and a Virtex 5 FPGA board. The CMOS sensor is a EV76C560 provided by e2v. This 1.3 Megapixel device offers novel pixel integration/readout modes and em- bedded image pre-processing capabilities including multiframe acquisition with various exposure times. Our approach consists of a hardware architecture with different algorithms: double exposure control during image capture, building of an HDR image by combining the…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputer scienceHardware platformReal-time computingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processingVideo camera02 engineering and technologyTone mapping[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processinglaw.invention[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessinglawHistogram0202 electrical engineering electronic engineering information engineeringHigh dynamic rangeFPGA[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingHardware architectureCMOS sensorLiquid-crystal displayreal timePixelbusiness.industryDynamic range020207 software engineeringHigh Dynamic RangeFrame rate[SPI.TRON] Engineering Sciences [physics]/Electronics[ SPI.TRON ] Engineering Sciences [physics]/Electronicsimage processing[SPI.TRON]Engineering Sciences [physics]/ElectronicsIEEE020201 artificial intelligence & image processingbusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingComputer hardware
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Scene-based noise reduction on a smart camera

2012

International audience; Raw output data from CMOS image sensors tends to exhibit significant noise called Fixed-Pattern Noise (FPN) due to on-die variations between pixel photodetectors. FPN is often corrected by subtracting its value, estimated through calibration, from the sensor's raw signal. This paper introduces an on-line scene-based technique for an improved FPN compensation which does not rely on calibration, and hence is more robust to the dynamic changes in the FPN which may occur slowly over time. Development has been done with a special emphasis on real-time hardware implementation on a FPGA-based smart camera. Experimental results on different scenes are depicted showing that t…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputer scienceNoise reductionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing01 natural sciencesSignalCompensation (engineering)010309 optics[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing0103 physical sciences0202 electrical engineering electronic engineering information engineeringComputer visionSmart cameraImage sensor[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingPixelNoise (signal processing)business.industry020208 electrical & electronic engineeringEmphasis (telecommunications)Artificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Noise estimation from digital step-model signal

2013

International audience; This paper addresses the noise estimation in the digital domain and proposes a noise estimator based on the step signal model. It is efficient for any distribution of noise because it does not rely only on the smallest amplitudes in the signal or image. The proposed approach uses polarized/directional derivatives and a nonlinear combination of these derivatives to estimate the noise distribution (e.g., Gaussian, Poisson, speckle, etc.). The moments of this measured distribution can be computed and are also calculated theoretically on the basis of noise distribution models. The 1D performances are detailed, and as our work is mostly dedicated to image processing, a 2D…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image Processingstep model02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingCCD sensornoise distributionsymbols.namesake[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processingdigital signalsalt and pepper noiseStatistics0202 electrical engineering electronic engineering information engineeringMedian filterImage noisePoisson noiseValue noiseNoise estimationMathematics[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingedge modelmultiplicative noiseNoise measurementNoise (signal processing)020206 networking & telecommunicationsComputer Graphics and Computer-Aided DesignNoise floorGaussian white noiseGradient noiseimpulse noiseGaussian noisenonlinear modelsymbols020201 artificial intelligence & image processingnoise estimatorAlgorithm[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingSoftware
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