Search results for "Image registration"

showing 10 items of 57 documents

Metodi automatici di analisi e caratterizzazione di esami radiologici del massiccio facciale.

L'obiettivo di questo lavoro è lo sviluppo di algoritmi e procedure di analisi di referti radiografici digitali di tipo CBCT delle strutture della mandibola e dell’apparato dentario. In particolare, mediante un’opportuna campagna di sperimentazione, in collaborazione con i reparti di radiologia ed odontoiatria del Policlinico di Palermo, è stata realizzata un procedura in grado di: • eliminare i problemi di sovrapponibilità dei referti tridimensionali effettuati in tempi successivi; • identificare lo spazio parodontale su indagini CBCT per la valutazione dei possibili difetti nello stesso e prevedere l’insorgenza di parodontiti. • individuare gli elementi di maggiore interesse medico caratt…

Registrazione di Immagini medicali Correlazione d'immagini tridimensionali Correlazione di Immagini Digitali Segmentazione Contorni Attivi Identificazione elementi dentari operatori morfologicimatrici di traslazione e rotazione procedure di analisi per immagini CBCT del maxillo faccialeMedical Image Registration Three-dimensional Image Correlation Digital Image Correlation Segmentation Active Contours Dental Identification Morphological Operators Traslation and rotation matirx CBCT maxillo facial image analysis procedures
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Invariant Feature Matching for Image Registration Application Based on New Dissimilarity of Spatial Features

2016

An invariant feature matching method is proposed as a spatially invariant feature matching approach. Deformation effects, such as affine and homography, change the local information within the image and can result in ambiguous local information pertaining to image points. New method based on dissimilarity values, which measures the dissimilarity of the features through the path based on Eigenvector properties, is proposed. Evidence shows that existing matching techniques using similarity metrics--such as normalized cross-correlation, squared sum of intensity differences and correlation coefficient--are insufficient for achieving adequate results under different image deformations. Thus, new…

Satellite ImageryComputer scienceComputer Visionlcsh:MedicineTransportation02 engineering and technology01 natural sciencesPattern Recognition Automated0202 electrical engineering electronic engineering information engineeringImage Processing Computer-Assistedlcsh:ScienceMultidisciplinaryApplied MathematicsSimulation and ModelingPhysicsClassical MechanicsDeformationPhysical SciencesEngineering and Technology020201 artificial intelligence & image processingAlgorithmsResearch ArticleNormalization (statistics)Matching (statistics)Computer and Information SciencesSimilarity (geometry)Imaging TechniquesImage registrationResearch and Analysis MethodsImage (mathematics)010309 optics0103 physical sciencesImage Interpretation Computer-AssistedComputer GraphicsComputer ImagingEigenvalues and eigenvectorsDamage Mechanicsbusiness.industrylcsh:RPattern recognitionEigenvaluesBoatsTarget DetectionAlgebraLinear AlgebraSubtraction TechniquePath (graph theory)lcsh:QAffine transformationArtificial intelligencebusinessEigenvectorsMathematicsHomography (computer vision)PLoS ONE
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Semi-automatic registration of retinal images based on line matching approach

2013

Accurate retinal image registration is essential to track the evolution of eye-related diseases. We propose a semiautomatic method based on features relying upon retinal graphs for temporal registration of retinal images. The features represent straight lines connecting vascular landmarks on the retina vascular tree: bifurcations, branchings, crossings, end points. In the built retinal graph, one straight line between two vascular landmarks indicates that they are connected by a vascular segment in the original retinal image. The locations of the landmarks are manually extracted to avoid the information loss due to errors in a retinal vessels segmentation algorithms. A straight line model i…

Semi-automatic registration of retinal images based on line matching approachGround truthSettore INF/01 - InformaticaMatching (graph theory)Computer sciencebusiness.industryFeature extractionImage registrationRetinalSimilarity measureTree (graph theory)chemistry.chemical_compoundchemistrySegmentationComputer visionArtificial intelligencebusinessProceedings of the 26th IEEE International Symposium on Computer-Based Medical Systems
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Prnu Pattern Alignment for Images and Videos Based on Scene Content

2019

This paper proposes a novel approach for registering the PRNU pattern between different camera acquisition modes by relying on the imaged scene content. First, images are aligned by establishing correspondences between local descriptors: The result can then optionally be refined by maximizing the PRNU correlation. Comparative evaluations show that this approach outperforms those based on brute-force and particle swarm optimization in terms of reliability, accuracy and speed. The proposed scene-based approach for PRNU pattern alignment is suitable for video source identification in multimedia forensics applications.

Settore ING-INF/05 - Sistemi Di Elaborazione Delle Informazioni021110 strategic defence & security studiesSettore INF/01 - Informaticabusiness.industryComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION0211 other engineering and technologiesPRNU SIFT image registration video stabilizationParticle swarm optimization02 engineering and technologyVideos Particle swarm optimization Image resolution Correlation Reliability Cameras SensorsIdentification (information)Content (measure theory)0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingComputer visionArtificial intelligencebusinessReliability (statistics)
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Composition of SIFT features for robust image representation

2010

In this paper we propose a novel feature based on SIFT (Scale Invariant Feature Transform) algorithm1 for the robust representation of local visual contents. SIFT features have raised much interest for their power of description of visual content characterizing punctual information against variation of luminance and change of viewpoint and they are very useful to capture local information. For a single image hundreds of keypoints are found and they are particularly suitable for tasks dealing with image registration or image matching. In this work we stretched the spatial coverage of descriptors creating a novel feature as composition of keypoints present in an image region while maintaining…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniComputer sciencebusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage registrationScale-invariant feature transformartificial intelligenceLuminanceimage annotationImage (mathematics)bag of wordsFeature (computer vision)SIFTvisual termsComputer visionArtificial intelligenceAffine transformationbusinessRepresentation (mathematics)semanticsImage representationFeature detection (computer vision)
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Fast, Reliable Head Tracking under Varying Illumination: An Approach Based on Robust Registration of Texture-Mapped 3D Models

2000

An improved technique for 3D head tracking under varying illumination conditions is proposed. The head is modeled as a texture mapped cylinder. Tracking is formulated as an image registration problem in the cylinder's texture map image. The resulting dynamic texture map provides a stabilized view of the face that can be used as input to many existing 2D techniques for face recognition, facial expressions analysis, lip reading, and eye tracking. To solve the registration problem in the presence of lighting variation and head motion, the residual error of registration is modeled as a linear combination of texture warping templates and orthogonal illumination templates. Fast and stable on-line…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniHead tracking. image registration
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Super-resolution-based magnification of endothelium cells from biomicroscope videos of the cornea

2018

We present a practical, robust, and effective pipeline to compute a high-resolution (HR) image of the corneal endothelium starting from a low-resolution (LR) video sequence obtained with a general purpose slit lamp biomicroscope. An image quality typical of dedicated and more expensive confocal microscopes is achieved via software magnification by exploiting information redundancy in the video sequence. In particular, the HR image is generated from the best LR frames, obtained by identifying the most suitable endothelium video subsequence using a support vector machine-based learning approach, followed by a robust graph-based frame registration. Results on long, real sequences show that the…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniImage fusionSettore INF/01 - InformaticaImage qualityComputer sciencebusiness.industryFrame (networking)ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage registrationMagnificationsuper-resolutionImage segmentationAtomic and Molecular Physics and Opticsslit lamp biomicroscope image enhancementComputer Science ApplicationsSupport vector machinecorneal endotheliumSoftwaremachine learningComputer visionimage mosaicingArtificial intelligenceElectrical and Electronic Engineeringbusiness
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Multi-modal Medical Image Registration by Local Affine Transformations

2018

Image registration is the process of finding the geometric transformation that, applied to the floating image, gives the registered image with the highest similarity to the reference image. Registering a pair of images involves the definition of a similarity function in terms of the parameters of the geometric transformation that allows the registration. This paper proposes to register a pair of images by iteratively maximizing the empirical mutual information through coordinate gradient descent. Hence, the registered image is obtained by applying a sequence of local affine transformations. Rather than adopting a uniformly spaced grid to select image blocks to locally register, as done by s…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniModalbusiness.industryComputer scienceImage Registration Mutual Information Medical ImagesImage registrationComputer visionArtificial intelligenceAffine transformationbusiness
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Medical image registration: Interpolations, similarities and optimizations strategies

2010

This paper presents a study conducted for evaluating different interpolation schemes, similarity metrics and optimization algorithms for the purpose of volumetric medical image registration. Each technique has been implemented to be plugged in a modular system. Rotation, translation and scale error has been measured to obtain a performance evaluation for all of the combinations of the considered techniques. Several experimental tests were conducted for validation both on synthetic and real datasets providing an exhaustive overview of the various strategies used.

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniSimilarity (geometry)business.industryComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage registrationTranslation (geometry)computer.software_genreHigh-definition videoMedical imagingMeasurement uncertaintyComputer visionMedical Image RegistrationArtificial intelligenceData miningbusinesscomputerRotation (mathematics)Interpolation2010 IEEE 23rd International Symposium on Computer-Based Medical Systems (CBMS)
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Effective and Efficient Interpolation for Mutual Information based Multimodality Elastic Image Registration

2009

Mutual information (MI) is a popular similarity metric for multimodality image registration purpose. However, it is negatively influenced by artifacts due to interpolation effects. As a result, registration algorithms performance could be affected. In this paper a novel interpolation scheme is presented. It is both effective and efficient. Effective because it limits the presence of local maxima in the mutual information curve, efficient because it is simple to compute being based on simple and optimized distance measures. The method is validated and compared against other techniques both from performance and time complexity persepectives. Differently from other reference works, which perfo…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniSimilarity (geometry)business.industryImage registrationMutual informationinterpolation mutual information elastic registration non-linear optimizationDistance measuresHistogramMetric (mathematics)Computer visionArtificial intelligencebusinessAlgorithmRigid transformationMathematicsInterpolation
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