Search results for "Signal and Image processing"

showing 10 items of 454 documents

Filtering and emission area identification in the Time Resolved Imaging data

2012

Abstract Time Resolved Imaging (TRI) acquisitions allow precise timing analysis of emission spots. Up to date technologies deeply challenge their isolation by hiding the weak ones, under sizing or over sizing visually detectable emission spots and finally by jeopardizing timing resolution. We report on an algorithm based on 1 and 2D signal processing tools which automates the identification of emission sites and optimizes separation between noise and useful signal, even for weak spots surrounding strong emission areas. The application of the algorithm on several sets of data from different types of devices and their results are also discussed.

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer science[INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing[SPI.NANO] Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronics[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technology01 natural sciencesImaging dataSignal[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing0103 physical sciences0202 electrical engineering electronic engineering information engineeringIsolation (database systems)[SPI.NANO]Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronics[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing010302 applied physicsSignal processingNoise (signal processing)business.industryPhoto EmissionStatic timing analysisPattern recognitionSizingIdentification (information)IC Failure AnalysisImage Thresholding[ SPI.NANO ] Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronics020201 artificial intelligence & image processingArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
researchProduct

Remote Photoplethysmography Based on Implicit Living Skin Tissue Segmentation

2016

International audience; Region of interest selection is an essential part for remote photoplethysmography (rPPG) algorithms. Most of the time, face detection provided by a supervised learning of physical appearance features coupled with skin detection is used for region of interest selection. However, both methods have several limitations and we propose to implicitly select living skin tissue via their particular pulsatility feature. The input video stream is decomposed into several temporal superpixels from which pulse signals are extracted. Pulsatility measure for each temporal superpixel is then used to merge pulse traces and estimate the photoplethysmogram signal. This allows to select …

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer science[SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging[INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing0206 medical engineering[INFO.INFO-IM] Computer Science [cs]/Medical Imaging02 engineering and technology[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]01 natural sciences010309 optics[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingSkin tissueRegion of interestPhotoplethysmogram0103 physical sciences[INFO.INFO-IM]Computer Science [cs]/Medical ImagingSegmentationComputer visionFace detection[ SDV.IB.IMA ] Life Sciences [q-bio]/Bioengineering/Imaging[ INFO.INFO-IM ] Computer Science [cs]/Medical Imagingbusiness.industrySupervised learning[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]020601 biomedical engineering[SDV.IB.IMA] Life Sciences [q-bio]/Bioengineering/ImagingArtificial intelligencebusiness
researchProduct

An evaluation framework and a benchmark for multi/hyperspectral image compression

2011

International audience; This paper benchmarks three multi/hyperspectral image compression approaches: the classic Multi-2D compression approach and two different implementations of 3D approach (Full 3D and Hybrid). All approaches are combined with a spectral PCA decorrelation stage to optimize performance. These three compression approaches are compared within a larger comparison framework than the conventionally used PSNR, which includes eight metrics divided into three families. The comparison is carried out with regard to variations in bitrates, spatial, and spectral dimensions variations of images. The time and memory consumption difference between the three approaches is also discussed…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer sciencebusiness.industryMultispectral image0211 other engineering and technologiesPattern recognition02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingcompressionwaveletsWavelet[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingCompression (functional analysis)Hyperspectral image compression0202 electrical engineering electronic engineering information engineeringBenchmark (computing)020201 artificial intelligence & image processingArtificial intelligencebusinessDecorrelation[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingMulti/hyperspectral images021101 geological & geomatics engineeringImage compression
researchProduct

Analysis of an Experimental Model of In Vitro Cardiac Tissue Using Phase Space Reconstruction

2014

International audience; The in vitro cultures of cardiac cells represent valuable models to study the mechanism of the arrhythmias at the cellular level. But the dynamics of these experimental models cannot be characterized precisely, as they include a lot of parameters that depend on experimental conditions. This paper is devoted to the investigation of the dynamics of an in vitro model using a phase space reconstruction. Our model, based on the heart cells of new born rats, generates electrical field potentials acquired using a microelectrode technology, which are analyzed in normal and under external stimulation conditions. Phase space reconstructions of electrical field potential signal…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingField (physics)Quantitative Biology::Tissues and OrgansChaoticHealth Informatics[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing030204 cardiovascular system & hematology01 natural sciences03 medical and health sciencesTheoretical physicsNonlinear system0302 clinical medicineDimension (vector space)[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingPhase space0103 physical sciencesSignal ProcessingAttractorEmbedding010306 general physicsBiological system[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingStatistical hypothesis testingMathematics
researchProduct

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)
researchProduct

Quadratic Objective Functions for Dichromatic Model Parameters Estimation

2017

International audience; In this paper, we present a novel method to estimate dichromatic model parameters from a single color image. Estimation of reflectance, shading and specularity has many applications such as shape recovery, specularity removal and facilitates classical image processing and computer vision tasks such as segmentation or classification. Our method is based on two successive and independent constrained quadratic programming steps to recover the parameters of the model. Compared to recent methods, our approach has the advantage to transform a complex inverse problem into two parralelizable optimization steps that are much easier to solve. We have compared our method with r…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingLinear programmingColor imagebusiness.industry[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]020206 networking & telecommunicationsImage processing02 engineering and technologyInverse problem[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Quadratic equation[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Specularity[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingRobustness (computer science)0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingComputer visionQuadratic programmingArtificial intelligencebusinessAlgorithmMathematics
researchProduct

Parameter-free adaptive step-size multiobjective optimization applied to remote photoplethysmography

2018

International audience; In this work, we propose to reformulate the objective function of Independent Component Analysis (ICA) to make it a better posed problem in the context of Remote photoplethysmography (rPPG). In recent previous works, linear combination coefficients of RGB channels are estimated maximizing the non-Gaussianity of ICA output components. However, in the context of rPPG a priori knowledge of the pulse signal can be incorporated into the component extraction algorithm. To this end, the contrast function of regular ICA is extended with a measure of periodicity formulated using autocorrelation. This novel semi-blind source extraction method for measuring rPPG has the interes…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingLinear programming[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputer science0206 medical engineeringAutocorrelation[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Context (language use)02 engineering and technology[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]020601 biomedical engineering01 natural sciencesMulti-objective optimizationIndependent component analysis010309 optics[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing0103 physical sciencesA priori and a posterioriRGB color modelLinear combinationAlgorithm
researchProduct

Detection and matching of curvilinear structures

2011

We propose an approach to curvilinear and wiry object detection and matching based on a new curvilinear region detector (CRD) and a shape context-like descriptor (COH). Standard methods for local patch detection and description are not directly applicable to wiry objects and curvilinear structures, such as roads, railroads and rivers in satellite and aerial images, vessels and veins in medical images, cables, poles and fences in urban scenes, stems and tree branches in natural images, since they assume the object is compact, i.e. that most elliptical patches around features cover only the object. However, wiry objects often have no flat parts and most neighborhoods include both foreground a…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingMatching (graph theory)Computer science[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technology01 natural sciences010309 optics[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingArtificial Intelligence0103 physical sciences0202 electrical engineering electronic engineering information engineeringSegmentationComputer visionComputingMilieux_MISCELLANEOUSCurvilinear coordinatesbusiness.industryObject (computer science)Object detectionTree (data structure)Signal ProcessingPattern recognition (psychology)020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionArtificial intelligenceScale (map)business[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingSoftware
researchProduct

Spatial correction in dynamic photon emission by affine transformation matrix estimation

2014

International audience; Photon emission microscopy and Time Resolved Imaging have proved their efficiency for defect localization on VLSI. A common process to find defect candidate locations is to draw a comparison between acquisitions on a normally working device and a faulty one. In order to be accurate and meaningful, this method requires that the acquisition scene remains the same between the two parts. In practice, it can be difficult to set. In this paper, a method to correct position by affine matrix transformation is suggested. It is based on image features detection, description and matching and affine transformation estimation.

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingMatching (graph theory)Computer science[INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing[SPI.NANO] Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronics02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingPosition (vector)020204 information systems0202 electrical engineering electronic engineering information engineeringComputer vision[SPI.NANO]Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronics[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingVery-large-scale integrationHarris affine region detectorbusiness.industryProcess (computing)Affine shape adaptationTransformation (function)020201 artificial intelligence & image processing[ SPI.NANO ] Engineering Sciences [physics]/Micro and nanotechnologies/MicroelectronicsArtificial intelligenceAffine transformationbusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
researchProduct

An optimized algorithm of image stitching in the case of a multi-modal probe for monitoring the evolution of scars

2013

International audience; We propose a new system that makes possible to monitor the evolution of scars after the excision of a tumorous dermatosis. The hardware part of this system is composed of a new optical innovative probe with which two types of images can be acquired simultaneously: an anatomic image acquired under a white light and a functional one based on autofluorescence from the protoporphyrin within the cancer cells. For technical reasons related to the maximum size of the area covered by the probe, acquired images are too small to cover the whole scar. That is why a sequence of overlapping images is taken in order to cover the required area. The main goal of this paper is to des…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingMatching (graph theory)Panorama[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScale-invariant feature transform[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technologyautofluorescence010501 environmental sciences01 natural sciencesImage stitching[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processingstitchingmulti-modal probe0202 electrical engineering electronic engineering information engineeringComputer visionProjection (set theory)[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing0105 earth and related environmental sciencesbusiness.industryFluorescenceScars evolutionmonitoringAutofluorescenceTransformation (function)020201 artificial intelligence & image processingArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingAlgorithmSPIE Proceedings
researchProduct