Search results for "computer vision"

showing 10 items of 2353 documents

A fast recursive algorithm to compute local axial moments

2001

The paper describes a fast algorithm to compute local axial moments used in the algorithm of discrete symmetry transform (DST). The basic idea is grounded on fast recursive implementation of respective linear filters by using the so-called primitive kernel functions since the moment computation can be performed in the framework of linear filtering. The main result is that the computation of the local axial moments is independent of the kernel size, i.e. of the order O(1) per data point (pixel). This result is of relevance whenever the DST is used to face with real time computer vision problems. The experimental results confirm the time complexity predicted by the theory.

Signal processingComputationMoment (mathematics)Control and Systems EngineeringFace (geometry)Signal ProcessingPoint (geometry)Computer Vision and Pattern RecognitionElectrical and Electronic EngineeringTime complexityAlgorithmSoftwareLinear filterMathematicsDiscrete symmetrySignal Processing
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Photoplethysmographic sensor with smoothed output signals

1999

A reflectance-type photoplethysmographic sensor probe connected to personal computer has been constructed and tested. Special algorithms and PC programs providing fast processing and smoothing of the output signals were developed. High-quality single period photoplethysmography signals were recorded from various locations of the body (fingers, forearm, neck). Clear differences in the shapes of detected single-period signals have been observed for different persons, and also for the same person at various measurement locations and before/after physical exercise.

Signal processingComputer sciencebusiness.industryPhotoplethysmogramPersonal computerElectronic engineeringDetection theoryComputer visionArtificial intelligencebusinessReflectivityComputing systemsSmoothingSPIE Proceedings
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Depth-of-Field Enhancement in Integral Imaging by Selective Depth-Deconvolution

2014

One of the major drawbacks of the integral imaging technique is its limited depth of field. Such limitation is imposed by the numerical aperture of the microlenses. In this paper, we propose a method to extend the depth of field of integral imaging systems in the reconstruction stage. The method is based on the combination of deconvolution tools and depth filtering of each elemental image using disparity map information. We demonstrate our proposal presenting digital reconstructions of a 3-D scene focused at different depths with extended depth of field.

Signal processingIntegral imagingOptical diffractionbusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONIterative reconstructionÒpticaCondensed Matter PhysicsElectronic Optical and Magnetic MaterialsNumerical apertureOpticsComputer visionDepth of fieldDeconvolutionArtificial intelligenceElectrical and Electronic EngineeringImage sensorbusinessGeologyJournal of Display Technology
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Electrocardiogram Signal Analysing - Delineation and Localization of ECG Component

2016

In this paper, we develop a new approach based on nonlinear filtering scheme (NLFS) on cardiac signal to evaluate a robust single-lead electrocardiogram (ECG) delineation system and waves localization method based on nonlinear filtering approach. This system is built in two phases, in the first phase, we proposed a mathematical model for detecting ECG features like QRS complex peak, P and T-waves onsets and ends from noise free of synthetic ECG signal. Later, we develop a theoretical model to obtain real approach for detecting these features from real noisy ECG signals. Our method has been evaluated on electrocardiogram signals of QT-MIT standard database, the QRS peak achieve sensitivity (…

Signal processingNoise (signal processing)Computer sciencebusiness.industryPhase (waves)Pattern recognitionSignalStandard deviationQRS complexComputer visionSensitivity (control systems)Artificial intelligenceEcg signalbusinessProceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies
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Observer-based finite-time fuzzy H∞ control for discrete-time systems with stochastic jumps and time-delays

2014

This paper is concerned with the problem of observer-based finite-time H ∞ control for a family of discrete-time Markovian jump nonlinear systems with time-delays represented by Takagi-Sugeno (T-S) model. The main contribution of this paper is to design an observer-based finite-time H ∞ controller such that the resulting closed-loop system is stochastic finite-time bounded and satisfies a prescribed H ∞ disturbance attenuation level over the given finite-time interval. Sufficient criteria on stochastic finite-time H ∞ stabilization via observer-based fuzzy state feedback are presented for the solvability of the problem, which can be tackled by a feasibility problem in terms of linear matrix…

Signal processingObserver (quantum physics)Finite-time H∞ controlTakagi-Sugeno (T-S) modelMarkovian jump systemsFuzzy control systemFuzzy logicFinite-time H∞ control; Markovian jump systems; Observer-based control; Takagi-Sugeno (T-S) model; Electrical and Electronic Engineering; Control and Systems Engineering; Software; Signal Processing; 1707Nonlinear systemobserver-based controlTakagi–Sugeno (T–S) modelDiscrete time and continuous timeControl and Systems EngineeringControl theoryBounded functionSignal ProcessingComputer Vision and Pattern RecognitionState observerElectrical and Electronic Engineeringfinite-time H∞ controlfinite-time H infinity controlObserver-based controlSoftware1707Mathematics
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Signal reconstruction, modeling and simulation of a vehicle full-scale crash test based on Morlet wavelets

2012

Creating a mathematical model of a vehicle crash is a task which involves considerations and analysis of different areas which need to be addressed because of the mathematical complexity of a crash event representation. Therefore, to simplify the analysis and enhance the modeling process, in this paper a novel wavelet-based approach is introduced to reproduce acceleration pulse of a vehicle involved in a crash event. The acceleration of a colliding vehicle is measured in its center of gravity-this crash pulse contains detailed information about vehicle behavior throughout a collision. Three types of signal analysis are elaborated here: time domain analysis (i.e. description of kinematics of…

Signal processingSignal reconstructionComputer scienceMultiresolution analysisCognitive NeuroscienceCrashComputer Science Applications1707 Computer Vision and Pattern RecognitionCrash testComputer Science ApplicationsMorlet wavelet; Multiresolution analysis; Signal reproduction; Vehicle crash modeling; Computer Science Applications1707 Computer Vision and Pattern Recognition; Cognitive Neuroscience; Artificial IntelligenceWaveletMorlet waveletArtificial IntelligenceFrequency domainTime domainSignal reproductionMorlet waveletMultiresolution analysisVehicle crash modelingSimulation
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Support Vector Machines Framework for Linear Signal Processing

2005

This paper presents a support vector machines (SVM) framework to deal with linear signal processing (LSP) problems. The approach relies on three basic steps for model building: (1) identifying the suitable base of the Hilbert signal space in the model, (2) using a robust cost function, and (3) minimizing a constrained, regularized functional by means of the method of Lagrange multipliers. Recently, autoregressive moving average (ARMA) system identification and non-parametric spectral analysis have been formulated under this framework. The generalized, yet simple, formulation of SVM LSP problems is particularized here for three different issues: parametric spectral estimation, stability of I…

Signal processingTelecomunicacionesSupport vector machinesSystem identificationLinear signal processingSpectral density estimationSpectral estimationSupport vector machineGamma filterControl and Systems EngineeringControl theoryComplex ARMASignal ProcessingAutoregressive–moving-average model3325 Tecnología de las TelecomunicacionesComputer Vision and Pattern RecognitionElectrical and Electronic EngineeringInfinite impulse responseDigital filterAlgorithmSoftwareParametric statisticsMathematics
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Progressive transmission of secured images with authentication using decompositions into monovariate functions

2014

International audience; We propose a progressive transmission approach of an image authenticated using an overlapping subimage that can be removed to restore the original image. Our approach is different from most visible water- marking approaches that allow one to later remove the watermark, because the mark is not directly introduced in the two-dimensional image space. Instead, it is rather applied to an equivalent monovariate representation of the image. Precisely, the approach is based on our progressive transmission approach that relies on a modified Kolmogorov spline network, and therefore inherits its advantages: resilience to packet losses during transmis- sion and support of hetero…

Signal processing[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing01 natural sciencesImage encryption010309 optics[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing0103 physical sciences0202 electrical engineering electronic engineering information engineeringComputer visionElectrical and Electronic EngineeringDigital watermarkingImage resolutionMathematicsSignal processingAuthenticationNetwork packetbusiness.industryWatermarkAtomic and Molecular Physics and OpticsComputer Science ApplicationsSpline (mathematics)Binary dataKolmogorov superposition theorem020201 artificial intelligence & image processingArtificial intelligencebusinessVisible watermarking[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Space–bandwidth product of optical signals and systems

1996

The space–bandwidth product (SW) is fundamental for judging the performance of an optical system. Often the SW of a system is defined only as a pure number that counts the degrees of freedom of the system. We claim that a quasi-geometrical representation of the SW in the Wigner domain is more useful. We also represent the input signal as a SW in the Wigner domain. For perfect signal processing it is necessary that the system SW fully embrace the signal SW.

Signal processingbusiness.industryComputer scienceBandwidth (signal processing)TopologyAtomic and Molecular Physics and OpticsElectronic Optical and Magnetic Materialssymbols.namesakeFourier transformOpticssymbolsComputer Vision and Pattern RecognitionSpatial frequencybusinessJournal of the Optical Society of America A
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A Direction/Orientation-Based Method for Shape Measurement by Shadow MoirÉ

2008

In this paper, a methodology to process fringe patterns is presented. The core of the signal processing technique is the use of the direction information, which is a modulo quantity that locally indicates the direction along which fringes grow at a maximum rate. By using this information, it was possible to perform adaptive and direction/orientation-based operations on fringe images to remove unwanted effects (mainly distortions at the image borders), to enhance the contrast, and to extract the phase information encoded. The method has been applied on shadow-moire interferograms with carrier fringes in order to measure the surface of small objects. The developed algorithm allows processing …

Signal processingbusiness.industryOrientation (computer vision)Computer sciencePhase distortionAstrophysics::Instrumentation and Methods for AstrophysicsPhase (waves)Process (computing)Adaptive filtersymbols.namesakeOpticsFourier transformsymbolsElectrical and Electronic EngineeringbusinessInstrumentationIEEE Transactions on Instrumentation and Measurement
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