Search results for " image processing."

showing 10 items of 2265 documents

Nouvelle tomographie Compton

2009

International audience

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[SDV.IB.IMA] Life Sciences [q-bio]/Bioengineering/Imaging[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging[INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingComputingMilieux_MISCELLANEOUS[ SDV.IB.IMA ] Life Sciences [q-bio]/Bioengineering/Imaging[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
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A classification approach to prostate cancer localization in 3T Multi-Parametric MRI

2016

International audience; Multiparametric-magnetic resonance imaging (mp-MRI) has demonstrated, in many studies, its potential in prostate cancer detection and analysis. We propose a supervised classification approach based on mp-MRI data base of 20 patients, in order to localize prostate cancer and to achieve a cartographic representation of the prostate voxels based on classification results. Proposed method provides a computer aided detection (CAD) software for prostatic cancer. For that, we have extracted varied features providing functional, anatomical and metabolic information helping the classifier to distinguish between three different classes ("Healthy", "Benign" and "Pathologic"). W…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[SPI] Engineering Sciences [physics][INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputer scienceSVMFeature extractionWord error ratecomputer.software_genre030218 nuclear medicine & medical imaging03 medical and health sciencesProstate cancer[SPI]Engineering Sciences [physics]0302 clinical medicine[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingProstateVoxelmedicine[ SPI ] Engineering Sciences [physics]Computer visionProstate cancermedicine.diagnostic_testbusiness.industryPattern recognitionMagnetic resonance imagingSpectramedicine.disease3. Good healthRandom forestSupport vector machinemedicine.anatomical_structuremp-MRIArtificial intelligencebusinesscomputer030217 neurology & neurosurgeryRandom forest
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A comparative study of noise effects in a FitzHugh-Nagumo circuit

2014

International audience; This paper focuses on the behaviour of a nonlinear FitzHugh-Nagumo circuit in the stochastic case that is in presence of noise and without deterministic driving. When the circuit is tuned below the Andronov-Hopf bifurcation, classical coherence res- onance signature is revealed. We compare the stochastic response of the system when the noise acts on two different parameters of the system. It is experimentally shown that an enhancement of the systems response can be achieved when the noise is directly added into the nonlinearity.

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[SPI] Engineering Sciences [physics][INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing[ NLIN.NLIN-CD ] Nonlinear Sciences [physics]/Chaotic Dynamics [nlin.CD][ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing[SPI.TRON] Engineering Sciences [physics]/Electronics[SPI.TRON]Engineering Sciences [physics]/Electronics[ SPI.TRON ] Engineering Sciences [physics]/Electronics[SPI]Engineering Sciences [physics][NLIN.NLIN-CD] Nonlinear Sciences [physics]/Chaotic Dynamics [nlin.CD][NLIN.NLIN-PS]Nonlinear Sciences [physics]/Pattern Formation and Solitons [nlin.PS][INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[NLIN.NLIN-PS] Nonlinear Sciences [physics]/Pattern Formation and Solitons [nlin.PS][NLIN.NLIN-CD]Nonlinear Sciences [physics]/Chaotic Dynamics [nlin.CD][ SPI ] Engineering Sciences [physics][ NLIN.NLIN-PS ] Nonlinear Sciences [physics]/Pattern Formation and Solitons [nlin.PS][SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
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CDnet 2014: An Expanded Change Detection Benchmark Dataset

2014

International audience; Change detection is one of the most important low-level tasks in video analytics. In 2012, we introduced the changedetection.net (CDnet) benchmark, a video dataset devoted to the evalaution of change and motion detection approaches. Here, we present the latest release of the CDnet dataset, which includes 22 additional videos (~70,000 pixel-wise annotated frames) spanning 5 new categories that incorporate challenges encountered in many surveillance settings. We describe these categories in detail and provide an overview of the results of more than a dozen methods submitted to the IEEE Change Detection Workshop 2014. We highlight strengths and weaknesses of these metho…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processingbusiness.industryComputer science[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingMotion detection[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingcomputer.software_genre[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingAnalyticsBenchmark (computing)Data miningbusinesscomputer[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingChange detection[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
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Cross-Media Color Reproduction and Display Characterization

2012

International audience; In this chapter, we present the problem of cross-media color reproduction, that is, how to achieve consistent reproduction of images in different media with different technologies. Of particular relevance for the color image processing community is displays, whose color properties have not been extensively covered in previous literature. Therefore, we go more in depth concerning how to model displays in order to achieve colorimetric consistency. The structure of this chapter is as follows: After a short introduction, we introduce the field of cross-media color reproduction, including a brief description of current standards for color management, the concept of colori…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processingbusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONColor reproductionCross media[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technologyBiologyColor management01 natural sciencesCharacterization (materials science)law.invention010309 opticsConsistency (database systems)[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processinglaw0103 physical sciences0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingColor image processingRelevance (information retrieval)Computer visionArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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eISP, une architecture de calcul programmable pour l'amélioration d'images sur téléphone portable.

2009

4 pages; Today's smart phones, with their embedded high-resolution video sensors, require computing capacities that are too high to easily meet stringent silicon area and power consumption requirements (some one and a half square millimeters and half a watt) especially when programmable components are used. To develop such capacities, integrators still rely on dedicated low resolution video processing components, whose drawback is low flexibility. With this in mind, our paper presents eISP {--} a new, fully programmable Embedded Image Signal Processor architecture, now validated in {TSMC~65nm} technology to achieve a capacity of {16.8~GOPs} at {233~MHz}, for {1.5~mm$^2$} of silicon area and…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processinglow power[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingCMOS[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingeISPSIMDvideo pipeimage processing[INFO.INFO-MC]Computer Science [cs]/Mobile ComputingMulti-SIMD[INFO.INFO-MC] Computer Science [cs]/Mobile Computing[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[ INFO.INFO-MC ] Computer Science [cs]/Mobile Computing[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
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eISP: a Programmable Processing Architecture for Smart Phone Image Enhancement

2009

4 pages; Today's smart phones, with their embedded high-resolution video sensors, require computing capacities that are too high to easily meet stringent silicon area and power consumption requirements (some one and a half square millimeters and half a watt) especially when programmable components are used. To develop such capacities, integrators still rely on dedicated low resolution video processing components, whose drawback is low flexibility. With this in mind, our paper presents eISP {--} a new, fully programmable Embedded Image Signal Processor architecture, now validated in {TSMC 65nm} technology to achieve a capacity of {16.8 GOPs} at {233 MHz}, for {1.5 mm$^2$} of silicon area and…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processinglow power[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingCMOSdemosaïcking[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingeISPmm²SIMDimage processingvideo pipesmall siliconMulti-SIMDcomputing tilemilliwatt[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingsensordemosaicingTSMC 65nm[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
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Camera-based measurement of relative image contrast in projection displays

2013

International audience; This research investigated the measured contrast of projection displays based on pictures taken by un-calibrated digital cameras under typical viewing conditions. A high-end radiometer was employed as a reference to the physical response of projection luminance. Checkerboard, gray scale and color complex test images with a range of the projector's brightness and contrast settings were projected. Two local and two global contrast metrics were evaluated on the acquired pictures. We used contrast surface plots and Pearson correlation to investigate the measured contrast versus the projector's brightness and contrast settings. The results suggested, as expected, the proj…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processingoptical projectors[INFO.INFO-TS] Computer Science [cs]/Signal and Image Processingprojection luminanceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingmeasured contrastradiometersImage color analysismetrics[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processingstatistical analysispicture acquisitioncamerasgray scaleBrightnessoptical variables measurementdigital cameracamera-based measurementRadiometry[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingdisplay devicesDigital camerasuncalibrated digital cameraglobal contrast metricsprojector brightness settingscheckerboardcolor complex test imagesrelative image contrastviewing conditionsradiometerimage processingCorrelationPearson correlationhigh-end radiometerprojection displayprojector contrast settings[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingprojection displayscontrast surface plotsstatistic based metrics
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AN APPROACH TO CORRECTING IMAGE DISTORTION BY SELF CALIBRATION STEREOSCOPIC SCENE FROM MULTIPLE VIEWS

2012

International audience; An important step in the analysis and interpretation of video scenes for recognizing scenario is the aberration corrections introduced during the image acquisition in order to provide and correct real image data. This paper presents an approach on distortion correction based on stereoscopic self calibration from images sequences by using a multi-camera system of vision (network cameras). This approach for correcting image distortion brings an elegant and robust technique with good accuracy. Without any knowledge of shooting conditions, the camera's parameters will be estimated. For this, the image key points of interest are extracted from different overlapping views …

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processingprojective rectification[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingImage qualityEpipolar geometryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processing[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technologyfundamental matrix[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingCamera auto-calibration0202 electrical engineering electronic engineering information engineeringComputer visionImage rectificationImage warpingImage restorationstereovision[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingMathematicsbusiness.industry020208 electrical & electronic engineeringAstrophysics::Instrumentation and Methods for AstrophysicsReal imageComputer Science::Computer Vision and Pattern Recognitionepipolar geometry020201 artificial intelligence & image processingArtificial intelligencedistortionbusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Definition of a mutual reference shape based on information theory and active contours

2013

In this paper, we propose to consider the estimation of a reference shape from a set of different segmentation results using both active contours and information theory. The reference shape is then defined as the minimum of a criterion that benefits from both the mutual information and the joint entropy of the input segmentations. This energy criterion is here justified using similarities between information theory quantities and area measures, and presented in a continuous variational framework. This framework brings out some interesting evaluation measures such as the specificity and sensitivity. In order to solve this shape optimization problem, shape derivatives are computed for each te…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processingsegmentation evaluation[ INFO.INFO-IM ] Computer Science [cs]/Medical Imaging[INFO.INFO-TS] Computer Science [cs]/Signal and Image Processingaverage shape[SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging[INFO.INFO-IM] Computer Science [cs]/Medical ImagingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingactive contours[SDV.IB.IMA] Life Sciences [q-bio]/Bioengineering/Imaging[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV]shape gradientsImage processingcardiac MRI.[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV][ INFO.INFO-TI ] Computer Science [cs]/Image Processingshape optimizationcardiac MRI[INFO.INFO-IM]Computer Science [cs]/Medical Imaging[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing[ SDV.IB.IMA ] Life Sciences [q-bio]/Bioengineering/Imaging[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processinginformation theory
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