Search results for "Color difference"

showing 10 items of 20 documents

An adaptive-PCA algorithm for reflectance estimation from color images

2008

This paper deals with the problem of spectral reflectance estimation from color camera outputs. Because the reconstruction of such functions is an inverse problem, stabilizing the reconstruction process is highly desirable. One way to do this is to decompose reflectance function on a basis functions like PCA. The present work proposes an algorithm making PCA adaptive in reflectance estimation from a color camera output. We propose to adapt the PCA basis derivation by selecting, for each sample, the more relevant elements from the training set elements. The adaptivity criterion is achieved by a likelihood measurement. Finally, the spectral reflectance estimation results are evaluated with th…

Basis (linear algebra)Color differenceEstimation theorybusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONBasis functionPattern recognitionIterative reconstructionInverse problemSample (graphics)Principal component analysisArtificial intelligencebusinessAlgorithmMathematics2008 19th International Conference on Pattern Recognition
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Influence of resin cement shade on the color and translucency of zirconia crowns

2020

Background Zirconia crowns are highly attractive for clinicians, although have poor translucency when used as single restorations, in addition to unknown effect of resin cement shade on final cemented crown shade. This study aimed to assess effect of resin cement opacity on color replication potential of different zirconia frameworks with target tooth color, in addition to different zirconia crowns translucency evaluation. Material and methods Twenty-four zirconia crown restorations were fabricated to restore single central maxillary incisor for 8 patients, divided into 3 groups according to color and type of zirconia used (white Zr core, colored Zr core and monolithic HT Zrcowns). Each gro…

CementProsthetic DentistryMaterials scienceColor differenceResearchmedicine.medical_treatment0206 medical engineering030206 dentistry02 engineering and technology:CIENCIAS MÉDICAS [UNESCO]020601 biomedical engineeringCrown (dentistry)03 medical and health sciences0302 clinical medicineUNESCO::CIENCIAS MÉDICASmedicineTooth colorCubic zirconiaSingle central maxillary incisorComposite materialGeneral DentistryResin cement
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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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Application of the S-CIELAB color model to processed and calibrated images with a colorimetric dithering method.

2009

This work uses the S-CIELAB color model to compare images that have been calibrated and processed using a colorimetric dithering method which simulates increments in viewing distance. Firstly, we obtain XYZ calibrated images by applying the appropriate color transformations to the original images. These transformations depend on whether the image is viewed on a display device or encoded by a capture device, for example. Secondly, we use a colorimetric dithering method consisting of a partitive additive mixing of XYZ tristimulus values. The number of dithered pixels depends on simulated viewing distance. The dithered tristimulus values are transformed to digital data to observe the dithering…

Color histogramPixelColor differencebusiness.industryComputer scienceColor imageColor normalizationDigital imagingColor balanceColor spaceAtomic and Molecular Physics and OpticsColor quantizationColor modelOpticsICC profileColor depthRGB color modelColor filter arrayDitherbusinessColorimetryImage resolutionOptics express
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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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Colorimetric Characterization of Mobile Devices for Vision Applications

2015

Purpose: Available applications for vision testing in mobile devices usually do not include detailed setup instructions, sacrificing rigor to obtain portability and ease of use. In particular, colorimetric characterization processes are generally obviated. We show that different mobile devices differ also in colorimetric profile and that those differences limit the range of applications for which they are most adequate. Methods: The color reproduction characteristics of four mobile devices, two smartphones (Samsung Galaxy S4, iPhone 4s) and two tablets (Samsung Galaxy Tab 3, iPad 4), have been evaluated using two procedures: 3D LUT (Look Up Table) and a linear model assuming primary constan…

Computer scienceColor reproductionColorSoftware portabilityRange (statistics)HumansComputer visionIndependence (probability theory)ÓpticaColor differencebusiness.industryVision TestsUsabilityColorimetric characterizationOphthalmologyScreenComputers HandheldLookup tableLinear Models3D lookup tableColorimetryArtificial intelligenceSmartphonebusinessTabletMobile deviceOptometry
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Multi-level contrast filtering in image difference metrics

2013

In this paper, we present a new metric to estimate the perceived difference in contrast between an original image and a reproduction. This metric, named weighted-level framework Δ E E (WLF-DEE), implements a multilevel filtering based on the difference of Gaussians model proposed by Tadmor and Tolhurst (2000) and the new Euclidean color difference formula in log-compressed OSA-UCS space proposed by Oleari et al. (2009). Extensive tests and analysis are presented on four different categories belonging to the well-known Tampere Image Database and on two databases developed at our institution, providing different distortions directly related to color and contrast. Comparisons in performance wi…

Difference of GaussiansColor differenceBiometricsbusiness.industryComputer scienceContrast (statistics)Pattern recognitionImage (mathematics)Metric (mathematics)Pattern recognition (psychology)Euclidean geometrySignal ProcessingArtificial intelligenceElectrical and Electronic EngineeringbusinessInformation SystemsEURASIP Journal on Image and Video Processing
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Freshness assessment of gilthead sea bream (Sparus aurata) by machine vision based on gill and eye color changes

2013

Abstract The fish freshness was evaluated using machine vision technique through color changes of eyes and gills of farmed and wild gilthead sea bream ( Sparus aurata ), being employed lightness ( L * ), redness ( a * ), yellowness ( b * ), chroma ( c * ), and total color difference (Δ E ) parameters during fish ice storage. A digital color imaging system, calibrated to provide accurate CIELAB color measurements, was employed to record the visual characteristics of eyes and gills. The region of interest was automatically selected using a computer program developed in MATLAB software. L * , b * , and Δ E of eyes increased with storage time, while c * decreased. The a * parameter of fish eyes…

FisheryGillLightnessIce storageColor differenceMachine visionColor changesEye colorFood scienceBiologyFood ScienceFish gillJournal of Food Engineering
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Visual acuity and color discrimination in patients with cataracts.

2020

Color vision tests can give information about pathological changes in eye structures. The purpose of our research was to study the color vision sensitivity and visual acuity changes before and after cataract surgery. We used a saturated Farnsworth D15 color vision arrangement test to check color sensitivity changes in confusion line directions. The test is easily perceptible (essential to eldery patients), and it is possible to check color sensitivity changes in tritan, protan, and deutan confusion line directions. The results were analyzed in several ways: by summing the color differences between adjacent caps according to Bowman and averaging the color difference vectors according to Ving…

MaleVisual acuitygenetic structuresColor visionmedicine.medical_treatmentVisual Acuity01 natural sciencesColor discriminationCataract010309 opticsOpticsCataracts0103 physical sciencesmedicineHumansIn patientChromatic scaleLeast-Squares AnalysisMathematicsAgedColor differencebusiness.industryCataract surgerymedicine.diseaseeye diseasesAtomic and Molecular Physics and OpticsElectronic Optical and Magnetic MaterialsOptometryRegression AnalysisFemalesense organsComputer Vision and Pattern Recognitionmedicine.symptombusinessColor PerceptionJournal of the Optical Society of America. A, Optics, image science, and vision
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Color memory matching in normal and red-green anomalous trichromat subjects

2001

The methods of simultaneous and successive color matching have been studied for a set of seven color reference samples by 15 protanomalous and 21 deuteranomalous trichromat subjects. From comparison between both populations and a group of 25 trichromat normal ones, investigated previously under similar experimental conditions [J. Perez–Carpinell et al. Color memory matching: time effect and other factors. Color Res Appl 1998;23:234–247], we can deduce the following. (a) For anomalous trichromat populations, as with a normal one, we find significant differences between simultaneous and successive color matching, p < 0.05. (b) If we consider the average of all the colors, we find that, while …

Matching (statistics)Color differencebusiness.industryColor visionGeneral Chemical EngineeringSignificant differenceTrichromacyHuman Factors and ErgonomicsGeneral ChemistryAstrophysicsColor matchingAnomalous trichromacyOpticsbusinessDelay timeMathematicsColor Research &amp; Application
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