Search results for "Computer Vision"

showing 10 items of 2353 documents

Automatic Unsupervised Segmentation of Retinal Vessels Using Self-Organizing Maps and K-Means Clustering

2011

In this paper an automatic unsupervised method for the segmentation of retinal vessels is proposed. A Self-Organizing Map is trained on a portion of the same image that is tested and K-means clustering algorithm is used to divide the map units in 2 classes. The entire image is again input for the Self-Organizing Map, and the class of each pixel will be the class of the best matching unit on the Self-Organizing Map. Finally, the vessel network is post-processed using a hill climbing strategy on the connected components of the segmented image. The experimental evaluation on the publicly available DRIVE database shows accurate extraction of vessels network and a good agreement between our segm…

Self-organizing mapGround truthSettore INF/01 - InformaticaPixelbusiness.industryComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONk-means clusteringScale-space segmentationPattern recognitionRetinal vessels Self-Organizing Map K-MeansSegmentationComputer visionArtificial intelligenceCluster analysisbusinessHill climbing
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Self-organizing maps: A new digital architecture

1991

An original hardware architecture implementing the self-organizing feature maps, which is one of the most powerful and efficent neural network algorithm, is presented. The architecture, contrary to the most investigated hardware implementations of neural networks, is a full digital one and it may be easily built by using the standard VLSI techniques.

Self-organizing mapHardware architectureVery-large-scale integrationArtificial neural networkComputer architectureFeature (computer vision)Computer scienceApplications architectureArchitectureDigital architecture
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A multiscale approach to automatic and unsupervised retinal vessel segmentation using Self-Organizing Maps

2016

In this paper an automatic unsupervised method for retinal vessel segmentation is described. Self-Organizing Map, modified Fuzzy C-Means, STAPLE algorithms and majority voting strategy were adopted to identify a segmentation of the retinal vessels. The performance of the proposed method was evaluated on the DRIVE database.

Self-organizing mapMajority ruleComputer science0206 medical engineeringComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technologySelf-organizing mapFuzzy logicCLAHE030218 nuclear medicine & medical imagingRetinal vessel03 medical and health scienceschemistry.chemical_compound0302 clinical medicineMajority votingSegmentationComputer visionComputingMethodologies_COMPUTERGRAPHICSFuzzy C-Mean1707Settore INF/01 - Informaticabusiness.industrySTAPLERetinal020601 biomedical engineeringRetinal vesselHuman-Computer InteractionComputer Networks and CommunicationchemistryAdaptive histogram equalizationArtificial intelligencebusinessSoftware
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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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Relative Vessel Motion Tracking using Sensor Fusion, Aruco Markers, and MRU Sensors

2017

This paper presents a novel approach for estimating the relative motion between two moving offshore vessels. The method is based on a sensor fusion algorithm including a vision system and two motion reference units (MRUs). The vision system makes use of the open-source computer vision library OpenCV and a cube with Aruco markers placed onto each of the cube sides. The Extended Quaternion Kalman Filter (EQKF) is used for bad pose rejection for the vision system. The presented sensor fusion algorithm is based on the Indirect Feedforward Kalman Filter for error estimation. The system is self-calibrating in the sense that the Aruco cube can be placed in an arbitrary location on the secondary ve…

Sensor fusionvision010504 meteorology & atmospheric sciencesComputer sciencebusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technologySensor fusion01 natural scienceslcsh:QA75.5-76.95Computer Science ApplicationsArucoMatch movingControl and Systems EngineeringModeling and Simulation0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingComputer visionKalman filterlcsh:Electronic computers. Computer scienceArtificial intelligencebusinessoffshore motion compensationSoftware0105 earth and related environmental sciencesModeling, Identification and Control: A Norwegian Research Bulletin
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A Layered Architecture for Sentiment Classification of Products Reviews in Italian Language

2017

The paper illustrates a system for the automatic classification of the sentiment orientation expressed into reviews written in Italian language. A proper stratification of linguistic resources is adopted in order to solve the lacking of an opinion lexicon specifically suited for the Italian language. Experiments show that the proposed system can be applied to a wide range of domains.

Sentiment analysis Text Classification of ReviewsSettore INF/01 - InformaticaComputer scienceOrientation (computer vision)business.industryMultitier architectureItalian languageSentiment analysis02 engineering and technologyLexiconcomputer.software_genreRange (mathematics)020204 information systems0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingArtificial intelligencebusinesscomputerNatural language processing
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<title>Restoration of a short-exposure image sequence degraded by atmospheric turbulence</title>

2000

This paper deals with the restoration of the shape of an object observed with a high-resolution infrared imaging device, through atmospheric turbulence. The propagation path is quite long (a few tenth kilometer) and the image is thus disturbed. A sequence of short-exposure images of the interesting object is recorded. We can see that the object shape fluctuates randomly during the sequence, but that its edges remain sharp, thanks to the very short exposure time. A bayesian analysis of the Fourier descriptors associated to the edges shows that the optimal shape is the one corresponding to the mean Fourier descriptors. We thus propose two ways to estimate this shape. The first one consists in…

SequenceActive contour modelGeographyMatching (graph theory)Position (vector)business.industryActive shape modelPath (graph theory)Computer visionPoint (geometry)Artificial intelligencebusinessImage restorationSPIE Proceedings
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Cloud motion detection from infrared satellite images

2002

The estimation of cloud motion from a sequence of satellite images can be considered a challenging task due to the complexity of phenomena implied. Being a non-rigid motion and implying non-linear events, most motion models are not suitable and new algorithms have to be developed. We propose a novel technique, combining a Block Matching Algorithm (BMA) and a best candidate block search along with a vector median regularisation.

SequenceComputer sciencebusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONMotion detectionCloud computingMotion (physics)Jump searchMotion estimationSatelliteComputer visionArtificial intelligencebusinessBlock-matching algorithmSPIE Proceedings
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Display of travelling 3D scenes from single integral-imaging capture

2016

Integral imaging (InI) is a 3D auto-stereoscopic technique that captures and displays 3D images. We present a method for easily projecting the information recorded with this technique by transforming the integral image into a plenoptic image, as well as choosing, at will, the field of view (FOV) and the focused plane of the displayed plenoptic image. Furthermore, with this method we can generate a sequence of images that simulates a camera travelling through the scene from a single integral image. The application of this method permits to improve the quality of 3D display images and videos.

SequenceIntegral imagingbusiness.industryPlane (geometry)ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONStereoscopyField of viewStereo displaylaw.inventionImage (mathematics)GeographylawComputer graphics (images)Computer visionArtificial intelligencebusinessSPIE Proceedings
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Computation and Display of 3D Movie From a Single Integral Photography

2016

Integral photography is an auto-stereoscopic technique that allows, among other interesting applications, the display of 3D images with full parallax and avoids the painful effects of the accommodation-convergence conflict. Currently, one of the main drawbacks of this technology is the need of a huge amount of data, which have to be stored and transmitted. This is due to the fact that behind every visual resolution unit, i.e. behind any microlens of an integral-photography monitor, between 100 and 300 pixels should appear. In this paper, we make use of an updated version of our algorithm, SPOC 2.0, to alleviate this situation. We propose the application of SPOC 2.0 for the calculation of co…

SequencePixelComputer sciencebusiness.industryComputationPhotographyFrame (networking)Field of viewImage processing02 engineering and technology021001 nanoscience & nanotechnologyCondensed Matter Physics01 natural sciencesElectronic Optical and Magnetic Materials010309 opticsComputer graphics (images)0103 physical sciencesComputer visionArtificial intelligenceElectrical and Electronic Engineering0210 nano-technologyParallaxbusinessJournal of Display Technology
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