Search results for " artificial intelligence"

showing 10 items of 1992 documents

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
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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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A new minimum trees-based approach for shape matching with improved time computing : application to graphical symbols recognition

2010

Recently we have developed a model for shape description and matching. Based on minimum spanning trees construction and specifics stages like the mixture, it seems to have many desirable properties. Recognition invariance in front shift, rotated and noisy shape was checked through median scale tests related to GREC symbol reference database. Even if extracting the topology of a shape by mapping the shortest path connecting all the pixels seems to be powerful, the construction of graph induces an expensive algorithmic cost. In this article we discuss on the ways to reduce time computing. An alternative solution based on image compression concepts is provided and evaluated. The model no longe…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingMatching (graph theory)[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputer scienceFeature extractionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingMinimum spanning tree[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingActive shape model0202 electrical engineering electronic engineering information engineeringDiscrete cosine transformComputingMilieux_MISCELLANEOUS[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingSpanning treebusiness.industry020206 networking & telecommunicationsPattern recognitionGraphShortest path problemGraph (abstract data type)020201 artificial intelligence & image processingArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingImage compression
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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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Source separation on hyperspectral cube applied to dermatology

2010

International audience; This paper proposes a method of quantification of the components underlying the human skin that are supposed to be responsible for the effective reflectance spectrum of the skin over the visible wavelength. The method is based on independent component analysis assuming that the epidermal melanin and the dermal haemoglobin absorbance spectra are independent of each other. The method extracts the source spectra that correspond to the ideal absorbance spectra of melanin and haemoglobin. The noisy melanin spectrum is fixed using a polynomial fit and the quantifications associated with it are reestimated. The results produce feasible quantifications of each source compone…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingMaterials science[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingHuman skin[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technology01 natural sciences010309 opticsAbsorbanceOptics[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing0103 physical sciences0202 electrical engineering electronic engineering information engineeringSource separationSource separation[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingPolynomial regressionIndependent Component Analysis.Spectral reflectanceKurtosisintegumentary systembusiness.industryNon-GaussianityHyperspectral imagingIndependent component analysisIndependent Component Analysis3. Good healthSkin patch020201 artificial intelligence & image processingbusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingVisible spectrum
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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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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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Kolmogorov Superposition Theorem and Wavelet Decomposition for Image Compression

2009

International audience; Kolmogorov Superposition Theorem stands that any multivariate function can be decomposed into two types of monovariate functions that are called inner and external functions: each inner function is associated to one dimension and linearly combined to construct a hash-function that associates every point of a multidimensional space to a value of the real interval $[0,1]$. These intermediate values are then associated by external functions to the corresponding value of the multidimensional function. Thanks to the decomposition into monovariate functions, our goal is to apply this decomposition to images and obtain image compression. We propose a new algorithm to decomp…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing010102 general mathematicsMathematical analysisWavelet transform02 engineering and technologyFunction (mathematics)[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingSuperposition theorem01 natural sciencesWavelet packet decompositionWavelet[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV]Dimension (vector space)[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 Processing0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingPoint (geometry)0101 mathematics[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingImage compressionMathematics
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