Search results for "image processing"

showing 10 items of 3285 documents

Image difference detection under varying illumination based on vector space and correlations

2012

Abstract We propose two methods to detect differences in images independently of local changes of intensity. The methods are based on calculating geometrical operators when images are considered as vectors. Operators can be expressed in terms of correlations for the possibility of optical implementations. The methods are invariant to changes of the form af ( x , y ) +  b , where a and b are arbitrary unknown parameters that may vary over the image f ( x , y ). Computer simulations show that the method works well when the illumination model is satisfied. Results from real images taken with a web camera show the robustness of the method.

business.industry02 engineering and technologyReal image01 natural sciencesAtomic and Molecular Physics and OpticsElectronic Optical and Magnetic Materials010309 opticsOpticsRobustness (computer science)0103 physical sciencesOptical correlator0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingElectrical and Electronic EngineeringInvariant (mathematics)businessAlgorithmMathematicsVector spaceOptik
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Learning-based multiresolution transforms with application to image compression

2013

In Harten's framework, multiresolution transforms are defined by predicting finer resolution levels of information from coarser ones using an operator, called prediction operator, and defining details (or wavelet coefficients) that are the difference between the exact and predicted values. In this paper we use tools of statistical learning in order to design a more accurate prediction operator in this framework based on a training sample, resulting in multiresolution decompositions with enhanced sparsity. In the case of images, we incorporate edge detection techniques in the design of the prediction operator in order to avoid Gibbs phenomenon. Numerical tests are presented showing that the …

business.industry020206 networking & telecommunicationsPattern recognition02 engineering and technologySample (graphics)Edge detectionGibbs phenomenonsymbols.namesakeWaveletOperator (computer programming)Control and Systems EngineeringCompression (functional analysis)Statistical learning theorySignal Processing0202 electrical engineering electronic engineering information engineeringsymbols020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionArtificial intelligenceElectrical and Electronic EngineeringbusinessSoftwareImage compressionMathematicsSignal Processing
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A LDR image expansion method for displaying on HDR screen

2013

International audience

business.industry020207 software engineering02 engineering and technologyTone mappingImage (mathematics)[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV]Computer graphics (images)[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV][ INFO.INFO-TI ] Computer Science [cs]/Image Processing0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingComputer visionArtificial intelligencebusinessComputingMilieux_MISCELLANEOUSMathematics
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Predicting human performance in interactive tasks by using dynamic models

2017

The selection of an appropriate sequence of activities is an essential task to keep student motivation and foster engagement. Usually, decisions in this respect are made by taking into account the difficulty of the activities, in relation to the student's level of competence. In this paper, we present a dynamic model that aims to predict the average performance of a group of students at solving a given series of maths problems. The system takes into account both student- and task-related features. This model was built and validated by using the data gathered in an experimental session that involved 64 participants solving a sequence of 26 arithmetic problems. The data collected from the fir…

business.industry05 social sciences050301 education02 engineering and technologyMachine learningcomputer.software_genreElectronic mailData modelingCorrelationDynamic models0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingArtificial intelligenceRemainderbusiness0503 educationCompetence (human resources)computer2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC)
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On the use of generalized harmonic means in image processing using multiresolution algorithms

2019

In this paper we design a family of cell-average nonlinear prediction operators that make use of the generalized harmonic means and we apply the resulting schemes to image processing. The new famil...

business.industryApplied MathematicsHarmonic meanStability (learning theory)Image processing010103 numerical & computational mathematics01 natural sciencesNonlinear predictionComputer Science Applications010101 applied mathematicsComputational Theory and Mathematics0101 mathematicsbusinessAlgorithmNonlinear operatorsSubdivisionMathematicsInternational Journal of Computer Mathematics
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Parallel distance transforms on pyramid machines: Theory and implementation

1990

Abstract A distance transform of a binary image is an array each of whose elements gives the distance from the corresponding pixel to the closest ‘1’ in the binary image. Distance transforms have uses in image matching and shape analysis, among other applications. We present a parallel algorithm for weighted distance transforms that runs particularly efficiently on hierarchical cellular-logic machines, a subclass of the architectures known as pyramid machines. The algorithm computes the 3–4 distance transform; however it can be readily adapted to the city-block (‘Manhattan’) and chessboard distance measures. The algorithm runs in O(M) time, for an M × M image. Since it avoids using arithmet…

business.industryBinary imageParallel algorithmImage processingDistance measuresControl and Systems EngineeringSignal ProcessingComputer visionComputer Vision and Pattern RecognitionArtificial intelligencePyramid (image processing)Jaro–Winkler distanceElectrical and Electronic EngineeringGilbert–Johnson–Keerthi distance algorithmbusinessAlgorithmDistance transformSoftwareMathematicsSignal Processing
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Detecting motion independent of the camera movement through a log-polar differential approach

1997

This paper is concerned with a differential motion detection technique in log-polar coordinates which allows object motion tracking independently of the camera ego-motion when camera focus is along the movement direction. The method does not use any explicit estimation of the motion field, which can be calculated afterwards at the moving points. The method, previously formulated in Cartesian coordinates, uses the log-polar coordinates, which allows the isolation of the object movement from the image displacement due to certain camera motions. Experimental results on a sequence of real images are included, in which a moving object is detected and optical flow is calculated in log-polar coord…

business.industryCamera matrixComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONOptical flowImage processingReal imageGeneralized coordinatesMatch movingMotion fieldCamera auto-calibrationMotion estimationPinhole camera modelComputer visionArtificial intelligenceImage sensorbusinessFocus (optics)Camera resectioning
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Perceptual image quality assessment using a normalized Laplacian pyramid

2016

business.industryComputer science0202 electrical engineering electronic engineering information engineeringLaplacian pyramid020206 networking & telecommunications020201 artificial intelligence & image processingPerceptual image qualityComputer vision02 engineering and technologyArtificial intelligencebusinessElectronic Imaging
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Visualization of Memory Map Information in Embedded System Design

2018

Data compression is a common requirement for displaying large amounts of information. The goal is to reduce visual clutter. The approach given in this paper uses an analysis of a data set to construct a visual representation. The visualization is compressed using the address ranges of the memory structure. This method produces a compressed version of the initial visualization, retaining the same information as the original. The presented method has been implemented as a Memory Designer tool for ASIC, FPGA and embedded systems using IP-XACT. The Memory Designer is a user-friendly tool for model based embedded system design, providing access and adjustment of the memory layout from a single v…

business.industryComputer science020207 software engineering02 engineering and technologyConstruct (python library)Memory mapVisualizationData visualizationApplication-specific integrated circuit0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingbusinessProgrammerField-programmable gate arrayComputer hardwareData compression2018 21st Euromicro Conference on Digital System Design (DSD)
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Mesh Visual Quality based on the combination of convolutional neural networks

2019

Blind quality assessment is a challenging issue since the evaluation is done without access to the reference nor any information about the distortion. In this work, we propose an objective blind method for the visual quality assessment of 3D meshes. The method estimates the perceived visual quality using only information from the distorted mesh to feed pre-trained deep convolutional neural networks. The input data is prepared by rendering 2D views from the 3D mesh and the corresponding saliency map. The views are split into small patches of fixed size that are filtered using a saliency threshold. Only the salient patches are selected as input data. After that, three pre-trained deep convolu…

business.industryComputer science020207 software engineeringPattern recognition02 engineering and technologyConvolutional neural networkRendering (computer graphics)SalientDistortion0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingSaliency map[INFO]Computer Science [cs]Artificial intelligencebusinessFeature learningComputingMilieux_MISCELLANEOUS
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