Search results for "SCALE"

showing 10 items of 5180 documents

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
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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
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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
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Cluster matching in time resolved imaging for VLSI analysis

2014

International audience; If scaling has the benefit of enabling manufacturers to design tomorrow's integrated circuits, from the failure analyst point of view it also has the drawback of making devices more complex. The test sequence for modern VLSI can be quite long, with thousands of vector. Dynamic photon emission databases can contain millions of photons representing thousands of state changes in the region of interest. Finding a candidate location where to perform physical analysis is quite challenging, especially if the fault occurs on a single vector. In this paper, we suggest a new methodology to find single vector fault in dynamic photon emission database. The process is applied at …

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingMatching (graph theory)[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputer science[SPI.NANO] Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronics[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technologyIntegrated circuitFault (power engineering)computer.software_genre01 natural sciencesk-nearest neighbors algorithmlaw.invention[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processinglaw0103 physical sciences0202 electrical engineering electronic engineering information engineeringPoint (geometry)[SPI.NANO]Engineering Sciences [physics]/Micro and nanotechnologies/MicroelectronicsCluster analysisComputer Science::Databases[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing010302 applied physicsVery-large-scale integrationProcess (computing)Computer engineering[ SPI.NANO ] Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronics020201 artificial intelligence & image processingData mining[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingcomputerProceedings of the 21th International Symposium on the Physical and Failure Analysis of Integrated Circuits (IPFA)
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Manufactured object sub-segmentation based on reflection motion estimation

2015

International audience; In computer vision, reflection is a long-standing problem, it covers image textures, makes original color difficult to recognize, complicates the understanding of the scene. Most of the time, it is considered as “noise”. Many methods are proposed in order to reduce or delete the reflection effects in the image, but generally, the performances are not quite satisfactory. While instead of working on “de-noising”, we propose a method to take advantage of moving reflections that can be used for different computer vision applications. For instance, the segmentation of reflective manufactured objects is presented in this paper. We focus on tracking reflection components an…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingSegmentation-based object categorizationbusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScale-space segmentationPattern recognition02 engineering and technologyImage segmentation01 natural sciencesScale space010309 opticsImage texture[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingRegion growingMotion estimation0103 physical sciences0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingComputer visionArtificial intelligenceReflection (computer graphics)businessMathematics
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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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THE HOMOLOGY OF DIGRAPHS AS A GENERALIZATION OF HOCHSCHILD HOMOLOGY

2010

J. Przytycki has established a connection between the Hochschild homology of an algebra $A$ and the chromatic graph homology of a polygon graph with coefficients in $A$. In general the chromatic graph homology is not defined in the case where the coefficient ring is a non-commutative algebra. In this paper we define a new homology theory for directed graphs which takes coefficients in an arbitrary $A-A$ bimodule, for $A$ possibly non-commutative, which on polygons agrees with Hochschild homology through a range of dimensions.

[ MATH.MATH-GT ] Mathematics [math]/Geometric Topology [math.GT]57M15 16E40 05C20Homology (mathematics)[ MATH.MATH-CO ] Mathematics [math]/Combinatorics [math.CO]Mathematics::Algebraic Topology01 natural sciencesCombinatoricsMathematics - Geometric TopologyMathematics::K-Theory and Homology[MATH.MATH-GT]Mathematics [math]/Geometric Topology [math.GT][MATH.MATH-CO]Mathematics [math]/Combinatorics [math.CO][ MATH.MATH-KT ] Mathematics [math]/K-Theory and Homology [math.KT]0103 physical sciencesFOS: MathematicsMathematics - CombinatoricsChromatic scale0101 mathematicsMathematics::Symplectic GeometryMathematicsAlgebra and Number TheoryHochschild homologyApplied Mathematics010102 general mathematicsGeometric Topology (math.GT)K-Theory and Homology (math.KT)Directed graphMathematics::Geometric TopologyGraphMathematics - K-Theory and HomologyPolygon[MATH.MATH-KT]Mathematics [math]/K-Theory and Homology [math.KT]BimoduleCombinatorics (math.CO)010307 mathematical physicsJournal of Algebra and Its Applications
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3D Displacements and Strains Solid Measurement based on the Surface Texture with a Scanner Laser

2013

International audience; The developments of non-contact measurement are today widely due to the unprecedented progress of optronic. The applications of these techniques are wide and varied for the 3D measurement of industrial products. In addition to the forms and dimensions, we show in this paper that the devices of laser scanning permit to measure displacements and deformations. In this case, it is necessary to follow a solid particle in its motion. It is then necessary to identify the particle between two configurations of the body before and after displacement. The method of greyscale patterns, obtained by applying a spray, is generally used. The originality of the proposed method is ba…

[ SPI.MECA.GEME ] Engineering Sciences [physics]/Mechanics [physics.med-ph]/Mechanical engineering [physics.class-ph]0209 industrial biotechnologyScannerMaterials scienceLaser scanningPoint cloud[PHYS.MECA.GEME]Physics [physics]/Mechanics [physics]/Mechanical engineering [physics.class-ph]02 engineering and technologySurface finishMetrology01 natural sciencesGrayscaleDisplacement (vector)010309 optics020901 industrial engineering & automation0103 physical sciencesPoint (geometry)Computer vision3D strain measurementLaser scanningGeneral Environmental SciencePixelbusiness.industry[SPI.MECA.GEME]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Mechanical engineering [physics.class-ph][ PHYS.MECA.GEME ] Physics [physics]/Mechanics [physics]/Mechanical engineering [physics.class-ph]General Earth and Planetary SciencesArtificial intelligencebusinessProcedia CIRP
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Strain fields measurement of non-rigid solid by scanning laser coupled with camera

2013

International audience; Abstract. Today, the techniques of measurement without contact by scanning laser are increasingly used. These techniques allow to measure 3D objects without contact and the measurement rates can reach few thousand points by second that is very adapted to complex shapes. To measure displacements and deformations, it is necessary to follow a solid particle in its motion between two configurations of the body before and after displacement. The method of stereovision based on grayscale patterns, obtained by applying a spray, is generally used. The results are obtained by two correlations: spatial and temporal correlations. An alternative method consists to use a scanner …

[ SPI.MECA.GEME ] Engineering Sciences [physics]/Mechanics [physics.med-ph]/Mechanical engineering [physics.class-ph]ScannerLaser scanningComputer sciencePoint cloudelastic Body02 engineering and technology01 natural sciencesGrayscaleDisplacement (vector)law.invention010309 optics0203 mechanical engineeringlawPosition (vector)0103 physical sciencesComputer visionstrain measurement[SPI.MECA.GEME] Engineering Sciences [physics]/Mechanics [physics.med-ph]/Mechanical engineering [physics.class-ph]Scanner Laserbusiness.industryLaser[SPI.MECA.GEME]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Mechanical engineering [physics.class-ph]020303 mechanical engineering & transportsArtificial intelligenceCubebusiness
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Multi-Kernel Implicit Curve Evolution for Selected Texture Regions Segmentation in VHR Satellite Images

2014

Very high resolution (VHR) satellite images provide a mass of detailed information which can be used for urban planning, mapping, security issues, or environmental monitoring. Nevertheless, the processing of this kind of image is timeconsuming, and extracting the needed information from among the huge quantity of data is a real challenge. For some applications such as natural disaster prevention and monitoring (typhoon, flood, bushfire, etc.), the use of fast and effective processing methods is demanded. Furthermore, such methods should be selective in order to extract only the information required to allow an efficient interpretation. For this purpose, we propose a texture region segmentat…

[INFO.INFO-AR]Computer Science [cs]/Hardware Architecture [cs.AR][INFO.INFO-AR] Computer Science [cs]/Hardware Architecture [cs.AR]Pixelbusiness.industryComputer science0211 other engineering and technologiesGraphics processing unitBoundary (topology)Scale-space segmentation02 engineering and technologyImage segmentationFuzzy logicImage texture11. Sustainability0202 electrical engineering electronic engineering information engineeringGeneral Earth and Planetary Sciences020201 artificial intelligence & image processingComputer visionSegmentation[ INFO.INFO-AR ] Computer Science [cs]/Hardware Architecture [cs.AR]Artificial intelligenceElectrical and Electronic EngineeringbusinessComputingMilieux_MISCELLANEOUS021101 geological & geomatics engineering
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