Search results for "Grayscale"

showing 10 items of 32 documents

Microstructure reconstruction using entropic descriptors

2009

A multi-scale approach to the inverse reconstruction of a pattern's microstructure is reported. Instead of a correlation function, a pair of entropic descriptors (EDs) is proposed for stochastic optimization method. The first of them measures a spatial inhomogeneity, for a binary pattern, or compositional one, for a greyscale image. The second one quantifies a spatial or compositional statistical complexity. The EDs reveal structural information that is dissimilar, at least in part, to that given by correlation functions at almost all of discrete length scales. The method is tested on a few digitized binary and greyscale images. In each of the cases, the persuasive reconstruction of the mic…

FOS: Computer and information sciencesStatistical Mechanics (cond-mat.stat-mech)General MathematicsComputer Vision and Pattern Recognition (cs.CV)Computer Science - Computer Vision and Pattern RecognitionGeneral EngineeringGeneral Physics and AstronomyBinary numberInverseFOS: Physical sciencesBinary patternGrayscaleImage (mathematics)CorrelationCorrelation function (statistical mechanics)Computer Science::Computer Vision and Pattern RecognitionStochastic optimizationStatistical physicsCondensed Matter - Statistical MechanicsMathematics
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Orientational analysis of planar fibre systems observed as a Poisson shot-noise process

2007

Summary We consider two-dimensional fibrous materials observed as a digital greyscale image. The problem addressed is to estimate the orientation distribution of unobservable thin fibres from a greyscale image modelled by a planar Poisson shot-noise process. The classical stereological approach is not straightforward, because the point intensities of thin fibres along sampling lines may not be observable. For such cases, Karkkainen et al. (2001) suggested the use of scaled variograms determined from grey values along sampling lines in several directions. Their method is based on the assumption that the proportion between the scaled variograms and point intensities in all directions of sampl…

HistologyBoolean modelbusiness.industryMathematical analysisShot noiseObservablePoisson distributionGrayscalePathology and Forensic Medicinesymbols.namesakePlanarOpticssymbolsVariogrambusinessBessel functionMathematicsJournal of Microscopy
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A stochastic shape and orientation model for fibres with an application to carbon nanotubes

2012

Methods are introduced for analysing the shape and orientation of planar fibres from greyscale images of fibrous systems. The sequence of image processing techniques needed for segmentation of fibres is described. The identified fibres were interpreted as deformed line segments for which two shape and two orientation parameters are estimated by the maximum likelihood method. The methods introduced are shown to perform quite well for simulated systems of deformed line segments with known properties. They were applied to TEM images of carbon nanotubes embedded in polycarbonate.

Materials scienceAcoustics and UltrasonicsMaterials Science (miscellaneous)General MathematicsCarbon nanotubesImage processingCarbon nanotube2D fibre identificationBinarizationGrayscaleDeformed line segmentslaw.inventionPlanarLine segmentlawRadiology Nuclear Medicine and imagingSegmentationPolycarbonateComposite materialInstrumentationlcsh:R5-920Orientation (computer vision)lcsh:MathematicsMultivariate von Mises distributionlcsh:QA1-939Computer Science::Computer Vision and Pattern Recognitionvisual_artSignal Processingvisual_art.visual_art_mediumComputer Vision and Pattern Recognitionlcsh:Medicine (General)BiotechnologyImage Analysis and Stereology
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Extraction and fusion of spectral parameters for face recognition

2011

This is the copy of journal's version originally published in Proc. SPIE 7877: http://spie.org/x10.xml?WT.svl=tn7. Reprinted with permission of SPIE. Many methods have been developed in image processing for face recognition, especially in recent years with the increase of biometric technologies. However, most of these techniques are used on grayscale images acquired in the visible range of the electromagnetic spectrum. The aims of our study are to improve existing tools and to develop new methods for face recognition. The techniques used take advantage of the different spectral ranges, the visible, optical infrared and thermal infrared, by either combining them or analyzing them separately …

Near Infrared[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingBiometrics[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingInfraredComputer scienceElectromagnetic spectrumFeature extractionImage processing02 engineering and technologyShort Wave Infrared[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingGrayscaleFacial recognition system[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing0202 electrical engineering electronic engineering information engineeringFeature descriptorComputer visionFace recognition[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingbusiness.industryNear-infrared spectroscopyVisibleFeature extraction020201 artificial intelligence & image processingArtificial intelligencefeature descriptorbusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing:Mathematics and natural science: 400::Information and communication science: 420::Simulation visualization signal processing image processing: 429 [VDP]
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Extract information of polarization imaging from local matching stereo

2010

Since polarization of light was used in the field of computer vision, the research of polarization vision is rapidly growing. Polarization vision has been shown to simplify some important image understanding tasks that can be more difficult to be performed with intensity vision. Furthermore, it has computational efficiency because it only needs grayscale images and can be easily applied by a simple optical setup. Nowadays, we can find various types of polarization cameras in the market. However, they are very expensive. In our work, we will study and develop a low price polarization camera setup with parallel acquisition using a stereo system. This system requires only two general cameras e…

PixelStereo camerasComputer sciencebusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONOptical polarizationPolarizerPolarization (waves)Grayscalelaw.inventionlawComputer Science::Computer Vision and Pattern RecognitionDegree of polarizationComputer visionArtificial intelligencebusinessComputer stereo vision2010 International Conference on Intelligent and Advanced Systems
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Choosing local matching score method for stereo matching based-on polarization imaging

2010

Polarization imaging is a powerful tool to observe hidden information from an observed object. It has significant advantages, such as computational efficiency (it only needs gray scale images) and can be easily applied by adding a polarizer in front of a camera. Many researchers used polarization in various areas of computer vision, such as object recognition, segmentation and so on. However, there is very little research in stereo vision based on polarization. Stereo vision is a well known technique for obtaining depth information from pairs of stereo digital images. One of the main focuses of research in this area is to get accurate stereo correspondences. In our work, we will study and d…

PixelStereo camerasComputer sciencebusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONStereoscopyGrayscalelaw.inventionDigital imageStereopsislawComputer visionArtificial intelligencebusinessComputer stereo visionStereo camera2010 The 2nd International Conference on Computer and Automation Engineering (ICCAE)
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Image Colorization Method Using Texture Descriptors and ISLIC Segmentation

2017

We present a new colorization method to assign color to a grayscale image based on a reference color image using texture descriptors and Improved Simple Linear Iterative Clustering (ISLIC). Firstly, the pixels of images are classified using Support Vector Machine (SVM) according to texture descriptors, mean luminance, entropy, homogeneity, correlation, and local binary pattern (LBP) features. Then, the grayscale image and the color image are segmented into superpixels, which are obtained by ISLIC to produce more uniform and regularly shaped superpixels than those obtained by SLIC, and the classified images are further post-processed combined with superpixles for removing erroneous classific…

Pixelbusiness.industryColor imageLocal binary patternsComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScale-space segmentationPattern recognitionImage segmentationGrayscaleImage textureComputer Science::Computer Vision and Pattern RecognitionArtificial intelligencebusinessCluster analysisComputingMethodologies_COMPUTERGRAPHICS
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Convolutional Neural Network-Based Human Movement Recognition Algorithm in Sports Analysis

2021

In order to analyse the sports psychology of athletes and to identify the psychology of athletes in their movements, a human action recognition (HAR) algorithm has been designed in this study. First, a HAR model is established based on the convolutional neural network (CNN) to classify the current action state by analysing the action information of a task in the collected videos. Secondly, the psychology of basketball players displaying fake actions during the offensive and defensive process is investigated by combining with related sports psychological theories. Then, the psychology of athletes is also analysed through the collected videos, so as to predict the next response action of the …

Process (engineering)convolutional neural network02 engineering and technologyGrayscaleConvolutional neural network050105 experimental psychologyTask (project management)0202 electrical engineering electronic engineering information engineeringPsychology0501 psychology and cognitive sciencesTime complexityGeneral PsychologyOriginal ResearchbiologyAthletessports analysis05 social sciencesbiology.organism_classificationhuman action recognitionBF1-990image recognitionAction (philosophy)sports psychologyRGB color model020201 artificial intelligence & image processingPsychologyAlgorithmFrontiers in Psychology
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On the orientational analysis of planar fibre systems from digital images

2002

The orientational characteristics of fibres in digital images are studied. The fibres are modelled by a planar Boolean model whose typical grain is a thick (coloured) fibre. The aim is to make stereological inference on the rose of directions of the unobservable central fibres from observations made on a digital image of the thick fibres. For central fibres, the relation between the rose of directions and the point intensity, observed on a sampling line, is known. We derive, under regularity conditions, the relation between the unobservable point intensity and the scaled variogram observed on the line in a binary and a greyscale image. Using such a relation, it is possible to draw inference…

Rose (mathematics)Histologybusiness.industryBinary numberGeometryGrayscalePathology and Forensic MedicineDigital imageOpticsPlanarLine (geometry)Point (geometry)businessVariogramMathematicsJournal of Microscopy
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Palmprint principal lines extraction

2014

The palmprint recognition has become a focus in biological recognition and image processing fields. In this process, the features extraction (with particular attention to palmprint principal line extraction) is especially important. Although a lot of work has been reported, the representation of palmprint is still an open issue. In this paper we propose a simple, efficient, and accurate palmprint principal lines extraction method. Our approach consists of six simple steps: normalization, median filtering, average filters along four prefixed directions, grayscale bottom-hat filtering, combination of bottom-hat filtering, binarization and post processing. The contribution of our work is a new…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniEngineeringGround truthBiometricsbusiness.industryFeature extractionsegmentationNormalization (image processing)Palm line extractionImage processingPattern recognitionGrayscalePalmprint; Palm line extraction; segmentation; biometricbiometricMedian filterComputer visionSegmentationArtificial intelligencePalmprintbusiness
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