Search results for "ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION"

showing 10 items of 982 documents

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
researchProduct

Preprocessing of region of interest localization based on local surface curvature analysis for three-dimensional reconstruction with multiresolution

2009

We present an approach to integrate a preprocessing step of the region of interest ROI localization into 3-D scanners laser or ste- reoscopic. The definite objective is to make the 3-D scanner intelligent enough to localize rapidly in the scene, during the preprocessing phase, the regions with high surface curvature, so that precise scanning will be done only in these regions instead of in the whole scene. In this way, the scanning time can be largely reduced, and the results contain only per- tinent data. To test its feasibility and efficiency, we simulated the prepro- cessing process under an active stereoscopic system composed of two cameras and a video projector. The ROI localization is…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION3d scanningStereoscopyImage processing0102 computer and information sciences02 engineering and technologyIterative reconstruction[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingCurvature01 natural sciencesVideo projectorsurface curvaturelaw.invention[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingRegion of interestlaw0202 electrical engineering electronic engineering information engineeringPreprocessorComputer visionImage resolution[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingComputingMethodologies_COMPUTERGRAPHICSbusiness.industryintelligent 3D scannerGeneral EngineeringAtomic and Molecular Physics and OpticsROI localisation010201 computation theory & mathematics020201 artificial intelligence & image processingArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingadaptive pattern
researchProduct

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
researchProduct

Registration of 3D and Multispectral Data for the Study of Cultural Heritage Surfaces

2013

International audience; We present a technique for the multi-sensor registration of featureless datasets based on the photogrammetric tracking of the acquisition systems in use. This method is developed for the in situ study of cultural heritage objects and is tested by digitizing a small canvas successively with a 3D digitization system and a multispectral camera while simultaneously tracking the acquisition systems with four cameras and using a cubic target frame with a side length of 500 mm. The achieved tracking accuracy is better than 0.03 mm spatially and 0.150 mrad angularly. This allows us to seamlessly register the 3D acquisitions and to project the multispectral acquisitions on th…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputer scienceMultispectral imageComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technologyclose range photogrammetryTracking (particle physics)computer.software_genrelcsh:Chemical technologyBiochemistryArticle3D digitizationAnalytical Chemistry[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing11. Sustainability2D-3D registration0202 electrical engineering electronic engineering information engineeringmultispectral imagingComputer visionlcsh:TP1-1185Electrical and Electronic EngineeringInstrumentationDigitization[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingMultispectral dataMultimediabusiness.industryFrame (networking)020207 software engineeringcultural heritageAtomic and Molecular Physics and Opticsoptical calibrationCultural heritagePhotogrammetrydigitization020201 artificial intelligence & image processingArtificial intelligencebusinesscomputer[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingSensors
researchProduct

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
researchProduct

Ontology-driven Image Analysis for Histopathological Images

2010

International audience; Ontology-based software and image processing engine must cooperate in new fields of computer vision like microscopy acquisition wherein the amount of data, concepts and processing to be handled must be properly controlled. Within our own platform, we need to extract biological objects of interest in huge size and high-content microscopy images. In addition to specific low-level image analysis procedures, we used knowledge formalization tools and high-level reasoning ability of ontology-based software. This methodology made it possible to improve the expressiveness of the clinical models, the usability of the platform for the pathologist and the sensitivity or sensibi…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputer science[INFO.INFO-IM] Computer Science [cs]/Medical ImagingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processingOntology (information science)[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]030218 nuclear medicine & medical imaging03 medical and health sciences[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]0302 clinical medicineSoftware[STAT.AP] Statistics [stat]/Applications [stat.AP][INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingDigital image processing[ INFO.INFO-TI ] Computer Science [cs]/Image Processing[INFO.INFO-IM]Computer Science [cs]/Medical ImagingComputer visionRDFImage analysis[STAT.AP]Statistics [stat]/Applications [stat.AP]Information retrieval[ INFO.INFO-IM ] Computer Science [cs]/Medical Imagingbusiness.industry[ STAT.AP ] Statistics [stat]/Applications [stat.AP][INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Usabilitycomputer.file_formatAutomatic image annotation[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV]030220 oncology & carcinogenesis[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]Artificial intelligencebusinesscomputer
researchProduct

Perceptual Spatial Uniformity Assessment of Projection Displays with a Calibrated Camera

2014

International audience; Spatial uniformity is one of the most important image quality attributes in visual experience of displays. In conventional researches, spatial uniformity was mostly measured with a radiometer and its quality was assessed with non-reference image quality metrics. Cameras are cheaper than radiometers and they can provide accurate relative measurements if they are carefully calibrated. In this paper, we propose and implement a work-flow to use a calibrated camera as a relative acquisition device of intensity to measure the spatial uniformity of projection displays. The camera intensity transfer functions for every projected pixels are recovered, so we can produce multip…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONColor and Imaging Conference
researchProduct

High Dynamic Range Real-time Vision System for Robotic Applications

2012

International audience; Robotics applications often requires vision systems capable of capturing a large amount of information related to a scene. With many camera sensors, the perception of information is limited in areas with strong contrasts. The High Dynamic Range (HDR) vision system can deal with these limitations. This paper describes the HDR-ARtiSt hardware platform (High Dynamic Range Advanced Real-time imaging System), a FPGA-based architecture that can produce a real- time high dynamic range video from successive image acquisition.

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
researchProduct

Automatic spatial and temporal organization of long range video sequences from low level motion features

2014

International audience; In this paper, we address the analysis of activities from long range video sequences. We present a method to automatically extract spatial and temporal structure from a video sequence from low level motion features. The scene layout is first extracted, with a set of regions that have homogeneous activities called Motion Patterns. These regions are then analyzed and the recurrent temporal motifs are extracted for each Motion Patterns. Preliminary results show that our method can accurately extract important temporal motifs from video surveillance sequences.

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
researchProduct

A smart camera for High Dynamic Range imaging

2013

International audience; A camera or a video camera is able to capture only a part of a high dynamic range scene information. The same scene can be almost totally 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 cam…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processingsmart camera[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONHigh dynamic range[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
researchProduct