Search results for " Pattern recognition"

showing 10 items of 1050 documents

Perceptual similarity between color images using fuzzy metrics

2016

A method to measure the similarity between color images is proposed.Correlation among the color image channels is taken into account.Proposed similarity measure is based on fuzzy metrics because of their advantages.The proposal matches well with the perceptual visual similarity between color images. In many applications of the computer vision field measuring the similarity between (color) images is of paramount importance. However, the commonly used pixelwise similarity measures such as Mean Absolute Error, Peak Signal to Noise Ratio, Mean Squared Error or Normalized Color Difference do not match well with perceptual similarity. Recently, it has been proposed a method for gray-scale image s…

Color histogramMean squared errorColor similarityComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technologySimilarity measureFuzzy logicLow level image processingFuzzy metricsSimilarity (network science)0202 electrical engineering electronic engineering information engineeringMedia TechnologyComputer visionElectrical and Electronic EngineeringMathematicsPerceptual image similarityColor differencebusiness.industryColor image020206 networking & telecommunicationsPattern recognitionColor imagingPeak signal-to-noise ratioPerceptual observationsColor image qualityFuzzy logicComputer Science::Computer Vision and Pattern RecognitionSignal Processing020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionArtificial intelligencebusinessJournal of Visual Communication and Image Representation
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Colour image segmentation and labeling through multiedit-condensing

1992

Abstract A new method is proposed for detecting and locating objects of interest within a colour scene under very strong variabilities in lighting conditions, object shape and pigmentation. The method is based on Nearest Neighbour classification and Multiedit-Condensing techniques and is applied to implement the vision subsystem of a robotic citric harvesting device. Experiments and results are reported showing the effectiveness of the method and illustrating its appropriateness to the proposed task.

Colour imageComputer scienceColor imagebusiness.industryObject (computer science)Task (project management)Artificial IntelligenceSignal ProcessingPattern recognition (psychology)SegmentationComputer visionComputer Vision and Pattern RecognitionArtificial intelligencebusinessSoftwarePattern Recognition Letters
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Prototype selection for the nearest neighbour rule through proximity graphs

1997

Abstract In this paper, the Gabriel and Relative Neighbourhood graphs are used to select a suitable subset of prototypes for the Nearest Neighbour rule. Experiments and results are reported showing the effectiveness of the method and comparing its performance to those obtained by classical techniques.

CombinatoricsArtificial IntelligenceGabriel graphSignal ProcessingNearest neighbourTheta graphComputer Vision and Pattern RecognitionNeighbourhood (mathematics)SoftwareMathematics
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Counting by Statistics on Search Trees: Application to Constraint Satisfaction Problems

1997

In 1975, Knuth proposed a simple statistical method for investigating search trees. We use this technique for estimating the number of solutions of constraint satisfaction problem CSP and boolean satisfiability problem SAT instances. We show that, depending on domain reductions, tree-based estimates have a lower variance than estimates based on uniform sampling from the search space. Nevertheless, because the variance remains extremely high in the general case, a confidence interval cannot be derived, but a lower bound of the number of solutions. These results are confirmed by many experiments.

Complexity of constraint satisfactionBacktrackingConstraint graphArtificial IntelligenceStatisticsConstraint satisfaction dual problemHybrid algorithm (constraint satisfaction)Local consistencyComputer Vision and Pattern RecognitionConstraint satisfactionConstraint satisfaction problemMathematicsTheoretical Computer ScienceIntelligent Data Analysis
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Local operators to detect regions of interest

1997

The performance of a visual system is strongly influenced by the information processing that is done in the early vision phase. The need exists to limit the computation on areas of interest to reduce the total amount of data and their redundancy. This paper describes a new method to drive the attention during the analysis of complex scenes. Two new local operators, based on the computation of local moments and symmetries, are combined to drive the selection. Experimental results on real data are also reported. © 1997 Elsevier Science B.V.

ComputationEarly visioncomputer.software_genreMachine learningFacial recognition systemSegmentationArtificial IntelligenceRedundancy (engineering)Selection (linguistics)AttentionSegmentationLimit (mathematics)Face recognitionElectrical and Electronic Engineering1707MathematicsSettore INF/01 - Informaticabusiness.industryInformation processingSignal ProcessingSymmetry operatorComputer Vision and Pattern RecognitionArtificial intelligenceData miningbusinesscomputerSoftwarePattern Recognition Letters
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Generic attribute deviation metric for assessing mesh simplification algorithm quality

2002

International audience; This paper describes an efficient method to compare two triangular meshes. Meshes considered here contain geometric features as well as other surface attributes such as material colors, texture, temperature, radiation, etc. Two deviation measurements are presented to assess the differences between two meshes. The first measurement, called geometric deviation, returns geometric differences. The second measurement , called attribute deviation, returns attribute differences regardless of the attribute type. In this paper we present an application of this method to the Mesh Simplification Algorithm (MSA) quality assessment according to the appearance attributes. This ass…

Computationmedia_common.quotation_subjectFeature extraction[INFO.INFO-GR] Computer Science [cs]/Graphics [cs.GR]02 engineering and technologySolid modeling[INFO.INFO-CG]Computer Science [cs]/Computational Geometry [cs.CG]Computer graphics[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]0202 electrical engineering electronic engineering information engineeringQuality (business)Polygon meshComputingMethodologies_COMPUTERGRAPHICSmedia_commonMathematicsbusiness.industry[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]020207 software engineeringPattern recognitionComputational geometry[INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR][INFO.INFO-CG] Computer Science [cs]/Computational Geometry [cs.CG]Metric (mathematics)020201 artificial intelligence & image processingArtificial intelligencebusinessAlgorithmProceedings. International Conference on Image Processing
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Seam Puckering Objective Evaluation Method for Sewing Process

2015

The paper presents an automated method for the assessment and classification of puckering defects detected during the preproduction control stage of the sewing machine or product inspection. In this respect, we have presented the possible causes and remedies of the wrinkle nonconformities. Subjective factors related to the control environment and operators during the seams evaluation can be reduced using an automated system whose operation is based on image processing. Our implementation involves spectral image analysis using Fourier transform and an unsupervised neural network, the Kohonen Map, employed to classify material specimens, the input images, into five discrete degrees of quality…

Computational Engineering Finance and Science (cs.CE)FOS: Computer and information sciencesComputer Vision and Pattern Recognition (cs.CV)Computer Science - Computer Vision and Pattern RecognitionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONComputer Science - Computational Engineering Finance and Science
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Attentional vs computational complexity measures in observing paintings

2009

Because of the great heterogeneity of subjects and styles, esthetic perception delineates a special and elusive field of research in vision, which represents an interesting challenge for cognitive science tools. With specific regard to the role of visual complexity, in this paper we present an experiment aimed to measure this dimension in a heterogeneous set of paintings. We compared perceived time complexity measures - based on a temporal estimation paradigm - with physical and statistical properties of the paintings, obtaining a strong correlation between psychological and computational results.

Computational complexity theoryVisionmedia_common.quotation_subjectMedicine in the ArtsVisual PhysiologyExperimental and Cognitive PsychologyField (computer science)PerceptionHumansAttentionDimension (data warehouse)Set (psychology)Time complexitymedia_commonSettore INF/01 - Informaticabusiness.industryDistance PerceptionComplexityForm PerceptionPattern Recognition VisualPattern recognition (psychology)PaintingsComputer Vision and Pattern RecognitionArtificial intelligenceFactor Analysis StatisticalPsychologybusinessPhotic StimulationCognitive psychology
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A Variational Approach for Denoising Hyperspectral Images Corrupted by Poisson Distributed Noise

2014

Poisson distributed noise, such as photon noise is an important noise source in multi- and hyperspectral images. We propose a variational based denoising approach, that accounts the vectorial structure of a spectral image cube, as well as the poisson distributed noise. For this aim, we extend an approach for monochromatic images, by a regularisation term, that is spectrally and spatially adaptive and preserves edges. In order to take the high computational complexity into account, we derive a Split Bregman optimisation for the proposed model. The results show the advantages of the proposed approach compared to a marginal approach on synthetic and real data.

Computational complexity theorybusiness.industryNoise reductionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONHyperspectral imagingPoisson distributionTerm (time)symbols.namesakeNoiseComputer Science::Computer Vision and Pattern RecognitionsymbolsComputer visionArtificial intelligenceMonochromatic colorCubebusinessAlgorithmMathematics
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A Battery-Free Smart Sensor Powered with RF Energy

2018

The development of Internet of Things (IoT) infrastructure and applications is stimulating advanced and innovative ideas and solutions, some of which are pushing the limits of state-of-the-art technology. The increasing demand for Wireless Sensor Network (WSN) that must be capable of collecting and sharing data wirelessly while often positioned in places hard to reach and service, motivates engineers to look for innovative energy harvesting and wireless power transfer solutions to implement battery-free sensor nodes. Due to the pervasiveness of RF (Radio Frequency) energy, RF harvesting that can reach out-of-sight places could be a key technology to wirelessly power IoT sensor devices, whic…

Computer Networks and CommunicationsComputer scienceInternet of ThingsEnergy Engineering and Power TechnologyRadio Frequency HarvestingIndustrial and Manufacturing EngineeringArtificial IntelligenceWireless Battery ChargerWirelessRenewable EnergyWireless power transferInstrumentationSustainability and the Environmentbusiness.industryRF power amplifierTransmitterElectrical engineeringComputer Science Applications1707 Computer Vision and Pattern RecognitionInternet of Things; Litium Ion Battery; Radio Frequency Harvesting; Wireless Battery Charger; Wireless Power Transfer; Wireless Sensor Networks; Artificial Intelligence; Computer Networks and Communications; Computer Science Applications1707 Computer Vision and Pattern Recognition; Energy Engineering and Power Technology; Renewable Energy Sustainability and the Environment; Industrial and Manufacturing Engineering; InstrumentationSensor nodeLitium Ion BatteryWireless Power TransferRadio frequencyInternet of ThingWireless Sensor NetworksbusinessEnergy harvestingWireless sensor network2018 IEEE 4th International Forum on Research and Technology for Society and Industry (RTSI)
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