Search results for "Pattern Recognition"

showing 10 items of 2301 documents

Interactive Image Retrieval Using Smoothed Nearest Neighbor Estimates

2010

Relevance feedback has been adopted by most recent Content Based Image Retrieval systems to reduce the semantic gap that exists between the subjective similarity among images and the similarity measures computed in a given feature space. Distance-based relevance feedback using nearest neighbors has been recently presented as a good tradeoff between simplicity and performance. In this paper, we analyse some shortages of this technique and propose alternatives that help improving the efficiency of the method in terms of the retrieval precision achieved. The resulting method has been evaluated on several repositories which use different feature sets. The results have been compared to those obt…

Computer sciencebusiness.industryFeature vectorRelevance feedbackPattern recognitionContent-based image retrievalcomputer.software_genrek-nearest neighbors algorithmSimilarity (network science)Feature (computer vision)Visual WordArtificial intelligenceData miningbusinessImage retrievalcomputer
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Non-linear Invertible Representation for Joint Statistical and Perceptual Feature Decorrelation

2000

The aim of many image mappings is representing the signal in a basis of decorrelated features. Two fundamental aspects must be taken into account in the basis selection problem: data distribution and the qualitative meaning of the underlying space. The classical PCA techniques reduce the statistical correlation using the data distribution. However, in applications where human vision has to be taken into account, there are perceptual factors that make the feature space uneven, and additional interaction among the dimensions may arise. In this work a common framework is presented to analyse the perceptual and statistical interactions among the coefficients of any representation. Using a recen…

Computer sciencebusiness.industryFeature vectormedia_common.quotation_subjectComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONPattern recognitionlaw.inventionLinear mapNonlinear systemInvertible matrixlawPerceptionHuman visual system modelArtificial intelligencebusinessDecorrelationmedia_common
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Optical technique for classification, recognition and identification of obscured objects

2010

Abstract The capability to classify, recognize and to identify objects from spatially low resolution images has high significance in security related applications especially in a case that recognition of camouflaged object is required. In this paper we present a novel approach in which the scenery containing obscured objects which we wish to classify, recognize or identify is illuminated by spatially coherent beam (e.g. laser) and therefore secondary speckles pattern is reflected from the objects. By special image processing algorithm developed for this research and which is basically based upon temporal tracking of the random speckle pattern one may extract the temporal signature of the ob…

Computer sciencebusiness.industryFourier opticsComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processingObject (computer science)Tracking (particle physics)Atomic and Molecular Physics and OpticsElectronic Optical and Magnetic MaterialsIdentification (information)Speckle patternOpticsPattern recognition (psychology)Electrical and Electronic EngineeringPhysical and Theoretical ChemistrybusinessImage resolutionOptics Communications
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Spatial/spectral information trade-off in hyperspectral images

2015

This paper shows an empirical analysis of the trade-off between the spectral and the spatial information content of hyperspectral images. The objective of this study is to provide some insights into how changes and variations of both resolutions may affect the information content of the resulting image. This is useful for different stages of hyperspectral image processing: from acquisition to final applications. We propose two alternative approaches to measure the information content of a hyperspectral image: first, a second order approximation where the data distribution is supposed to be Gaussian, and secondly a higher order approximation where no assumption about the data distribution is…

Computer sciencebusiness.industryGaussianHyperspectral imagingPattern recognitionsymbols.namesakeFull spectral imagingsymbolsEntropy (information theory)Computer visionArtificial intelligencebusinessSpatial analysisImage resolution2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
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Quality-preserving low-cost probabilistic 3D denoising with applications to Computed Tomography

2021

AbstractWe propose a pipeline for a synthetic generation of personalized Computer Tomography (CT) images, with a radiation exposure evaluation and a lifetime attributable risk (LAR) assessment. We perform a patient-specific performance evaluation for a broad range of denoising algorithms (including the most popular Deep Learning denoising approaches, wavelets-based methods, methods based on Mumford-Shah denoising etc.), focusing both on accessing the capability to reduce the patient-specific CT-induced LAR and on computational cost scalability. We introduce a parallel probabilistic Mumford-Shah denoising model (PMS), showing that it markedly-outperforms the compared common denoising methods…

Computer sciencebusiness.industryGaussianPipeline (computing)Deep learningNoise reductionProbabilistic logicPattern recognitionReduction (complexity)symbols.namesakeWaveletScalabilitysymbolsArtificial intelligencebusiness
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Classification Boundary Approximation by Using Combination of Training Steps for Real-Time Image Segmentation

2007

We propose a method of real-time implementation of an approximation of the support vector machine decision rule. The method uses an improvement of a supervised classification method based on hyperrectangles, which is useful for real-time image segmentation. We increase the classification and speed performances using a combination of classification methods: a support vector machine is used during a pre-processing step. We recall the principles of the classification methods and we evaluate the hardware implementation cost of each method. We present our learning step combination algorithm and results obtained using Gaussian distributions and an example of image segmentation coming from a part …

Computer sciencebusiness.industryGaussianScale-space segmentationPattern recognitionImage processingLinear classifierImage segmentationDecision ruleMachine learningcomputer.software_genreSupport vector machinesymbols.namesakesymbolsOne-class classificationArtificial intelligencebusinesscomputerGaussian process
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Fingerprint Registration Using Specialized Genetic Algorithms

2005

One of the most common problem to realize a robust matching algorithm in an Automated Fingerprint Identification System (AFIS) is the images registration. In this paper a fingerprints registration method based on a specialized genetic algorithm (GA) is proposed. A global transformation between two fingerprint images is performed using genetic data evolutions based on specialized mutation rate and solution refining. An AFIS including the above method has been developed and tested on two different fingerprint databases: NIST 4 ink-on-paper and self optical scanned. The obtained experimental results show that the proposed approach is comparable with literature systems working on medium quality…

Computer sciencebusiness.industryGenetic dataImage registrationPattern recognitionBiometricsfingerprint orientationFingerprintGenetic algorithmNISTGlobal transformationArtificial intelligencebusinessAutomated fingerprint identificationAlgorithmsBlossom algorithmEUROCON 2005 - The International Conference on "Computer as a Tool"
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Real-Time Human Pose Estimation from Body-Scanned Point Clouds

2015

International audience; This paper presents a novel approach to estimate the human pose from a body-scanned point cloud. To do so, a predefined skeleton model is first initialized according to both the skeleton base point and its torso limb obtained by Principal Component Analysis (PCA). Then, the body parts are iteratively clustered and the skeleton limb fitting is performed, based on Expectation Maximization (EM). The human pose is given by the location of each skeletal node in the fitted skeleton model. Experimental results show the ability of the method to estimate the human pose from multiple point cloud video sequences representing the external surface of a scanned human body; being r…

Computer sciencebusiness.industryHuman pose estimationPoint cloudComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]TorsoMissing data3D pose estimation[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]medicine.anatomical_structure[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Expectation–maximization algorithmPrincipal component analysismedicineComputer visionPoint (geometry)Artificial intelligencebusinessskeleton modelPoseComputingMethodologies_COMPUTERGRAPHICSpoint cloud
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Divisive normalization image quality metric revisited.

2010

Structural similarity metrics and information-theory-based metrics have been proposed as completely different alternatives to the traditional metrics based on error visibility and human vision models. Three basic criticisms were raised against the traditional error visibility approach: (1) it is based on near-threshold performance, (2) its geometric meaning may be limited, and (3) stationary pooling strategies may not be statistically justified. These criticisms and the good performance of structural and information-theory-based metrics have popularized the idea of their superiority over the error visibility approach. In this work we experimentally or analytically show that the above critic…

Computer sciencebusiness.industryImage qualityMachine visionPoolingNormalization (image processing)Wavelet transformImage processingImage enhancementMachine learningcomputer.software_genreAtomic and Molecular Physics and OpticsImage contrastElectronic Optical and Magnetic MaterialsOpticsComputer Vision and Pattern RecognitionArtificial intelligencebusinesscomputerJournal of the Optical Society of America. A, Optics, image science, and vision
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Three-dimensional Fuzzy Kernel Regression framework for registration of medical volume data

2013

Abstract In this work a general framework for non-rigid 3D medical image registration is presented. It relies on two pattern recognition techniques: kernel regression and fuzzy c-means clustering. The paper provides theoretic explanation, details the framework, and illustrates its application to implement three registration algorithms for CT/MR volumes as well as single 2D slices. The first two algorithms are landmark-based approaches, while the third one is an area-based technique. The last approach is based on iterative hierarchical volume subdivision, and maximization of mutual information. Moreover, a high performance Nvidia CUDA based implementation of the algorithm is presented. The f…

Computer sciencebusiness.industryImage registrationMutual informationMachine learningcomputer.software_genreFuzzy logicCUDANon-rigid registration Fuzzy regression Mutual information Interpolation GPU computingArtificial IntelligenceSignal ProcessingPattern recognition (psychology)Kernel regressionComputer Vision and Pattern RecognitionArtificial intelligenceData miningGeneral-purpose computing on graphics processing unitsCluster analysisbusinesscomputerSoftwareInterpolationPattern Recognition
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