Search results for "Color space"

showing 10 items of 36 documents

On the uniform sampling of CIELAB color space and the number of discernible colors

2013

This paper presents a useful algorithmic strategy to sample uniformly the CIELAB color space based on close packed hexagonal grid. This sampling scheme has been used successfully in different research works from computational color science to color image processing. The main objective of this paper is to demonstrate the relevance and the accuracy of the hexagonal grid sampling method applied to the CIELAB color space. The second objective of this paper is to show that the number of color samples computed depends on the application and on the color gamut boundary considered. As demonstration, we use this sampling to support a discussion on the number of discernible colors related to a JND.

Color histogram[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONcomputational color imagingColor balance[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technologyperceptually uniform color spaceColor space01 natural sciences010309 optics[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingICC profile0103 physical sciencesColor depth[ INFO.INFO-TI ] Computer Science [cs]/Image Processing0202 electrical engineering electronic engineering information engineering3D close packed hexagonal gridComputer visionSamplingComputingMilieux_MISCELLANEOUS[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingComputingMethodologies_COMPUTERGRAPHICSMathematicsColor differencebusiness.industry020207 software engineeringColor quantizationColor modelArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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A video-based real-time vehicle counting system using adaptive background method

2008

International audience; This paper presents a video-based solution for real time vehicle detection and counting system, using a surveillance camera mounted on a relatively high place to acquire the traffic video stream.The two main methods applied in this system are: the adaptive background estimation and the Gaussian shadow elimination. The former allows a robust moving detection especially in complex scenes. The latter is based on color space HSV, which is able to deal with different size and intensity shadows. After these two operations, it obtains an image with moving vehicle extracted, and then operation counting is effected by a method called virtual detector.

Computer scienceGaussianComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technologyHSL and HSVColor spaceVideo analysisShadow eliminationAdaptive background estimationImage (mathematics)symbols.namesake0502 economics and businessShadow0202 electrical engineering electronic engineering information engineeringComputer visionSurveillance camera050210 logistics & transportationPixelbusiness.industry05 social sciencesDetectorVirtual detectorsymbols020201 artificial intelligence & image processingArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Efficient Skin Detection under Severe Illumination Changes and Shadows

2011

International audience; This paper presents an efficient method for human skin color detection with a mobile platform. The proposed method is based on modeling the skin distribution in a log-chromaticity color space which shows good invariance properties to changing illumination. The method is easy to implement and can cope with the requirements of real-world tasks such as illumination variations, shadows and moving camera. Extensive experiments show the good performance of the proposed method and its robustness against abrupt changes of illumination and shadows.

Computer sciencebusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]020207 software engineering02 engineering and technologyFace detectionColor spaceInvariance to illumination[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Robustness (computer science)0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingComputer visionArtificial intelligenceLog-chromaticity color spaceColor detectionbusinessFace detectionSkin detectionComputingMethodologies_COMPUTERGRAPHICS
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Color illusions also deceive CNNs for low-level vision tasks: Analysis and implications.

2019

The study of visual illusions has proven to be a very useful approach in vision science. In this work we start by showing that, while convolutional neural networks (CNNs) trained for low-level visual tasks in natural images may be deceived by brightness and color illusions, some network illusions can be inconsistent with the perception of humans. Next, we analyze where these similarities and differences may come from. On one hand, the proposed linear eigenanalysis explains the overall similarities: in simple CNNs trained for tasks like denoising or deblurring, the linear version of the network has center-surround receptive fields, and global transfer functions are very similar to the human …

Computer sciencemedia_common.quotation_subjectIllusionColor spaceConvolutional neural network050105 experimental psychology03 medical and health sciences0302 clinical medicinePerceptionHumans0501 psychology and cognitive sciencesVision Ocularmedia_commonArtificial neural networkbusiness.industryOptical illusion05 social sciencesIllusionsSensory SystemsOphthalmologyVision scienceHuman visual system modelArtificial intelligenceNeural Networks Computerbusiness030217 neurology & neurosurgeryVision research
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Euclid Preparation. XIV. The Complete Calibration of the Color–Redshift Relation (C3R2) Survey: Data Release 3

2021

Stanford, S. A., et al.

Cosmology and Nongalactic Astrophysics (astro-ph.CO)[PHYS.ASTR.IM]Physics [physics]/Astrophysics [astro-ph]/Instrumentation and Methods for Astrophysic [astro-ph.IM]Calibration (statistics)FOS: Physical sciencesAstrophysicsAstrophysics::Cosmology and Extragalactic AstrophysicsColor space217101 natural sciencesCosmologyLarge-scale structure010309 optics[PHYS.ASTR.CO]Physics [physics]/Astrophysics [astro-ph]/Cosmology and Extra-Galactic Astrophysics [astro-ph.CO]galaxy spectroscopySettore FIS/05 - Astronomia e AstrofisicaSpitzer Space Telescope0103 physical sciencesDISTRIBUTIONSAstrophysics::Solar and Stellar AstrophysicsInstrumentation and Methods for Astrophysics (astro-ph.IM)PHOTOMETRIC REDSHIFTS010303 astronomy & astrophysicsWeak gravitational lensingAstrophysics::Galaxy AstrophysicsPhysicsHardware_MEMORYSTRUCTURESAstrophysics::Instrumentation and Methods for AstrophysicsEuclidAstronomy and AstrophysicsRedshiftGalaxyCosmologySpace and Planetary ScienceGalaxy spectroscopyDark energyAstrophysics - Instrumentation and Methods for AstrophysicsAstrophysics - Cosmology and Nongalactic Astrophysics
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Optimizing colormaps with consideration for color vision deficiency to enable accurate interpretation of scientific data

2018

Color vision deficiency (CVD) affects more than 4% of the population and leads to a different visual perception of colors. Though this has been known for decades, colormaps with many colors across the visual spectra are often used to represent data, leading to the potential for misinterpretation or difficulty with interpretation by someone with this deficiency. Until the creation of the module presented here, there were no colormaps mathematically optimized for CVD using modern color appearance models. While there have been some attempts to make aesthetically pleasing or subjectively tolerable colormaps for those with CVD, our goal was to make optimized colormaps for the most accurate perce…

FOS: Computer and information sciences0301 basic medicineBrightnessVisual perceptionVisionComputer scienceComputer Vision and Pattern Recognition (cs.CV)Computer Science - Computer Vision and Pattern Recognitionlcsh:MedicineSocial SciencesColor Vision Defects01 natural sciencesMass SpectrometryAnalytical ChemistrySecondary Ion Mass SpectrometrySpectrum Analysis TechniquesMathematical and Statistical TechniquesPsychologyComputer visionlcsh:ScienceData ProcessingMultidisciplinaryPhysicsClassical MechanicsOther Quantitative Biology (q-bio.OT)Quantitative Biology - Other Quantitative BiologyChemistryPhysical SciencesRegression AnalysisSensory PerceptionInformation TechnologyStatistics (Mathematics)AlgorithmsColor PerceptionResearch ArticleComputer and Information SciencesColor visionColorFluid MechanicsLinear Regression AnalysisColor spaceResearch and Analysis MethodsContinuum Mechanics010309 optics03 medical and health sciencesSine Waves0103 physical sciencesHumansStatistical MethodsFluid FlowVision OcularHueColor Visionbusiness.industrylcsh:RBiology and Life SciencesFluid Dynamics030104 developmental biologyFOS: Biological scienceslcsh:QArtificial intelligencebusinessMathematical FunctionsMathematicsPhotic StimulationSoftwareNeurosciencePLOS ONE
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Color image quality assessment measure using multivariate generalized Gaussian distribution

2014

This paper deals with color image quality assessment in the reduced-reference framework based on natural scenes statistics. In this context, we propose to model the statistics of the steer able pyramid coefficients by a Multivariate Generalized Gaussian distribution (MGGD). This model allows taking into account the high correlation between the components of the RGB color space. For each selected scale and orientation, we extract a parameter matrix from the three color components sub bands. In order to quantify the visual degradation, we use a closed-form of Kullback-Leibler Divergence (KLD) between two MGGDs. Using "TID 2008" benchmark, the proposed measure has been compared with the most i…

FOS: Computer and information sciencesColor histogramColor imagebusiness.industryComputer Vision and Pattern Recognition (cs.CV)Computer Science - Computer Vision and Pattern RecognitionPattern recognitionColor spaceRGB color spacesymbols.namesakesymbolsPyramid (image processing)Artificial intelligencebusinessDivergence (statistics)Gaussian processGeneralized normal distributionMathematics
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On color image quality assessment using natural image statistics

2014

Color distortion can introduce a significant damage in visual quality perception, however, most of existing reduced-reference quality measures are designed for gray scale images. In this paper, we consider a basic extension of well-known image-statistics based quality assessment measures to color images. In order to evaluate the impact of color information on the measures efficiency, two color spaces are investigated: RGB and CIELAB. Results of an extensive evaluation using TID 2013 benchmark demonstrates that significant improvement can be achieved for a great number of distortion type when the CIELAB color representation is used.

FOS: Computer and information sciencesColor histogrambusiness.industryColor imageComputer Vision and Pattern Recognition (cs.CV)Computer Science - Computer Vision and Pattern RecognitionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONColor balanceFalse colorColor spaceICC profileColor depthRGB color modelComputer visionArtificial intelligencebusinessMathematics
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2014

The majority of next-generation sequencing short-reads can be properly aligned by leading aligners at high speed. However, the alignment quality can still be further improved, since usually not all reads can be correctly aligned to large genomes, such as the human genome, even for simulated data. Moreover, even slight improvements in this area are important but challenging, and usually require significantly more computational endeavor. In this paper, we present CUSHAW3, an open-source parallelized, sensitive and accurate short-read aligner for both base-space and color-space sequences. In this aligner, we have investigated a hybrid seeding approach to improve alignment quality, which incorp…

GeneticsMultidisciplinarySource codeHeuristic (computer science)business.industrymedia_common.quotation_subjectPipeline (computing)Sequence alignmentColor spaceBiologyRanking (information retrieval)SoftwarebusinessAlgorithmAlignment-free sequence analysismedia_commonPLOS ONE
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Modelling the appearance of chromatic environment using hyperspectral imaging

2013

Color of objects is a spectral composition of incident light source, reflection properties of the object itself, and spectral tuning of the eye. Light sources with different spectral characteristics can produce metameric representation of color; however most variable in this regard is vision. Pigments of color vision are continuously bleached by different stimuli and optical density of the pigment is changed, while continuous conditions provide an adaptation and perception of white. Special cases are color vision deficiencies which cover almost 8 % of male population in Europe. Hyperspectral imaging allows obtaining the spectra of the environment and modelling the performance of the dichrom…

GeographyOpticsPrimary colorColor constancyDominant wavelengthColor visionbusiness.industryColor balanceColor temperaturebusinessSpectral colorCIE 1931 color spaceRemote sensingSPIE Proceedings
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