Rafael Huertas
Universidad de Granada, Departamento de Optica, Faculty Member
- I am a associate professor at University of Granada. My research interest are: colorimetry, texture, image, color vis... moreI am a associate professor at University of Granada. My research interest are: colorimetry, texture, image, color vision, color difference formulae, color spaces, color in food, etc.edit
Several colour-difference formulas have been proposed since the last recommendation of CIEDE2000 by the "Commission Internationale de L'Eclairage" (CIE) in 2001. Some of them have been tested using the same dataset used to... more
Several colour-difference formulas have been proposed since the last recommendation of CIEDE2000 by the "Commission Internationale de L'Eclairage" (CIE) in 2001. Some of them have been tested using the same dataset used to fit them. Thus, it is of great interest to check the performance of these formulas with new experimental datasets. On the other hand, some previous studies show that many colour-difference formulas perform quite badly in the very small colour difference range of 0 to 1 CIELAB units. This paper pursues these two goals. The colour-difference formulas DIN99d, OSA-GP, OSA-GP Euclidean (OSA-GPE), CAM02-SCD and CAM02-UCS are tested with a new experimental dataset, which has been carried out in the Laboratoire Hubert Curien of Saint Etienne (France) in two different modes, physical metallic samples and virtual samples displayed in a LCD monitor. This new dataset is composed by 390 colour pairs arranged around 16 colour centres with colour differences in the range 0.14 to 2.14 CIELAB units, with an average value of 0.80. In this work only just noticeable differences have been considered from this dataset. The results show a bad performance of all studied colour-difference formulas for just noticeable colour differences, in agreement with previous studies. Further research must be conducted to fit colourdifference formulae to this important range of colour differences.
Research Interests:
Research Interests:
Research Interests:
We previously reported the performance of four color difference equations around the CIE 1978 blue color center (NCSU-B1) using various statistical measures. In this study we employed the standardized residual sum of squares (STRESS)... more
We previously reported the performance of four color difference equations around the CIE 1978 blue color center (NCSU-B1) using various statistical measures. In this study we employed the standardized residual sum of squares (STRESS) index to test the performance of twelve color-difference formulae using two experimental NCSU datasets. The first dataset (NCSU-B1) included 66 sample pairs around the CIE 1978 blue color center and the second dataset (NCSU- 2) contained 69 sample pairs around 13 color centers. In the first dataset 26 observers made a total of 5148 assessments of sample pairs with small color differences (ΔE*ab<5) while the second dataset involved 20,700 assessments by 100 observers from four different geographical regions of the world (25 in each region). Each pair in both sets was assessed by each color normal observer in three separate sittings on separate days and the average of assessments was calculated. For the samples in the first dataset a custom AATCC standard gray scale was employed to assess the magnitude of difference between colored samples. A third-degree polynomial equation was used to convert gray scale ratings to visual differences (ΔV). In the second study a novel perceptually linear gray scale was developed and a linear function was used to obtain visual differences. Based on the analysis of STRESS index results the DIN99d equation gave the best results for both datasets, and the CIELAB equation the worst.
Research Interests:
AIC 2004 Color and Paints, Interim Meeting of the International Color Association, Proceedings Investigation of simulated texture effect on perceived color differences Rafael HUERTAS,* María José RIVAS,* Ana YEBRA,* María del Mar PÉREZ,*... more
AIC 2004 Color and Paints, Interim Meeting of the International Color Association, Proceedings Investigation of simulated texture effect on perceived color differences Rafael HUERTAS,* María José RIVAS,* Ana YEBRA,* María del Mar PÉREZ,* Manuel MELGOSA,* Manuel ...
Research Interests:
Scattered colorimetry, i.e., multi-angle and multi-wavelength absorption spectroscopy performed in the visible spectral range, was used to map three kinds of liquids: extra virgin olive oils, frying oils, and detergents in water. By... more
Scattered colorimetry, i.e., multi-angle and multi-wavelength absorption spectroscopy performed in the visible spectral range, was used to map three kinds of liquids: extra virgin olive oils, frying oils, and detergents in water. By multivariate processing of the spectral data, the liquids could be classified according to their intrinisic characteristics: geographic area of extra virgin olive oils, degradation of frying oils,
Research Interests:
Research Interests:
Research Interests:
Research Interests:
This paper analyzes, through computational simulations, which spectral filters increase the number of discernible colors (NODC) of subjects with normal color vision, as well as red–green anomalous trichromats and dichromats. The filters... more
This paper analyzes, through computational simulations, which spectral filters increase the number of discernible colors (NODC) of subjects with normal color vision, as well as red–green anomalous trichromats and dichromats. The filters are selected from a set of filters in which we have modeled spectral transmittances. With the selected filters we have carried out simulations performed using the spectral reflectances captured either by a hyperspectral camera or by a spectrometer. We have also studied the effects of these filters on color coordinates. Finally, we have simulated the results of two widely used color blindness tests: Ishihara and Farnsworth–Munsell 100 Hue (FM100). In these analyses the selected filters are compared with the commercial filters from EnChroma and VINO companies. The results show that the increase in NODC with the selected filters is not relevant. The simulation results show that none of these chosen filters help color vision deficiency (CVD) subjects to ...
Research Interests: Mathematics, Computer Science, Artificial Intelligence, Analytical Chemistry, Computer Vision, and 13 moreColorimetry, Medicine, Sensors, Color Vision, Color blindness, Hyperspectral Imaging, Color Blindness, Spectral Imaging, Electrical And Electronic Engineering, Hue, Chromatic Scale, Color difference, and Trichromacy
ABSTRACT Different approach to texture characterization can be considered. In this work texture are analyzed through second order statistical measurements based on the Grey-Level Co-occurrence Matrix proposed by Haralick [1]. By this... more
ABSTRACT Different approach to texture characterization can be considered. In this work texture are analyzed through second order statistical measurements based on the Grey-Level Co-occurrence Matrix proposed by Haralick [1]. By this method is possible to compute 22 different features to describe texture. Usually, in previous works, only 5 features are considered among the complete set, but no reasons are exposed for that selection. In this work, using Principal Component Analysis, the set of features is studied and 5 features, different from former, are proposed as the most convenient describing and characterizing the considered textures. Finally, the relationship between the proposed features and perception of texture is analyzed.
Research Interests:
Research Interests:
The improvement of the CIEDE2000 color-difference formula with respect to CIELAB has been experimentally tested using 10 color pairs which were specifically designed with this goal by Dr. D.H. Alman (CIE TC 1-47, chairman). The merit of... more
The improvement of the CIEDE2000 color-difference formula with respect to CIELAB has been experimentally tested using 10 color pairs which were specifically designed with this goal by Dr. D.H. Alman (CIE TC 1-47, chairman). The merit of these two formulas and the inter-observer experimental variability were measured using the Standardized Residual Sum of Squares (STRESS) index. Experiments were performed in two different laboratories, using the 9-steps gray scales for “Color Change” and “Staining” manufactured by the American Association for Testing Chemists and Colorists, and the Society of Dyers and Colourists. Observations were performed under standardized D65 sources by 21 inexperienced observers with non-defective color vision. The results found in both laboratories employing the two 9-steps gray scales were similar, and indicated a clear improvement of CIEDE2000 upon CIELAB, as was expected. The inter-observer variability in our experiments was considerably high, even higher than the predictions made using CIEDE2000. This means that CIEDE2000 (but not CIELAB) predicted our average-observer's results better than individual observers as a group. Current results encourage the use of the CIEDE2000 color-difference formula in industrial and applied colorimetry, including food color research.
Research Interests:
Spectral transmittances of three new photochromatic lenses have been measured at different activation states produced by the four luminous sources of a VeriVide CAC 120 cabinet. The greatest transmittance changes were found for the UV and... more
Spectral transmittances of three new photochromatic lenses have been measured at different activation states produced by the four luminous sources of a VeriVide CAC 120 cabinet. The greatest transmittance changes were found for the UV and D65 sources. These transmittances changes lead to average CIELAB color differences lower than 6 CIELAB units for the 24 chips of a GretagMacbeth color
Research Interests:
This paper presents colourimetric analyses of 6 standard soil-colour charts (1372 chips) from different manufacturers, editions, and degrees of use. The CIELAB hab, L*, and C*ab were found to have significant (analysis of variance, P <... more
This paper presents colourimetric analyses of 6 standard soil-colour charts (1372 chips) from different manufacturers, editions, and degrees of use. The CIELAB hab, L*, and C*ab were found to have significant (analysis of variance, P < 0.05) variations among tested charts, and the Munsell hue, value, and chroma measured in most chips varied from their notation by as much as 1 unit. This discrepancy can be attributed to printing differences and/or colour fading. The Munsell loci of constant hue and chroma plotted in CIELAB colour space showed that colour fading is not uniform, so that visual steps between neighbouring chips change, and constant hue and chroma lines become deformed. The colour difference between chips identically designated in two charts ranged from 0.94 CIEDE2000 units (above perception threshold) for charts from the same manufacturer and degree of use, to 3.72 CIEDE2000 units for old charts from 2 different manufacturers. Chips from old charts became yellowish, d...
Research Interests:
... MM Pérez A. Yebra, R Huertas, M. Melgosa, H. García-Toledo*, F. Carrillo* Departamento de Óptica. Facultad de Ciencias. ... 10. García JM, Gutiérrez, F., Castellano, JM; Perdiguero, S. Albi, MA Influence of store temperature on fruit... more
... MM Pérez A. Yebra, R Huertas, M. Melgosa, H. García-Toledo*, F. Carrillo* Departamento de Óptica. Facultad de Ciencias. ... 10. García JM, Gutiérrez, F., Castellano, JM; Perdiguero, S. Albi, MA Influence of store temperature on fruit ripening and olive oil quality. J. Agric. ...
Acceso de usuarios registrados. Acceso de usuarios registrados Usuario Contraseña. ...
Special effect coatings have been increasingly used in many industries (e.g. automotive, plastics industry) over the past two decades. The measurement of perceived color differences on such coatings cannot be done by means of traditional... more
Special effect coatings have been increasingly used in many industries (e.g. automotive, plastics industry) over the past two decades. The measurement of perceived color differences on such coatings cannot be done by means of traditional color-difference formulas (e.g. CMC(l:c), CIEDE2000, AUDI2000) as they lack to consider distinct optical properties such as coarseness, glint and goniochromatism. However, there is a need to ensure quality and colorimetric accuracy when designing and processing special effect coatings. In this paper, we present a psychophysical experiment intended to serve as a basis for future work on a new generation of color-difference formula(s) for multiple viewing geometries (viewing and illumination angle). We are especially interested in assessing whether judging under a single geometry can lead to different results as judging under several (two) geometries, i.e. whether the sum is more than its part.
Research Interests:
We have performed spectroradiometric color measurements at different positions on the floor of two lights booths under two light sources. Uniformity provided by these light booths is enough acceptable for most practical color applications... more
We have performed spectroradiometric color measurements at different positions on the floor of two lights booths under two light sources. Uniformity provided by these light booths is enough acceptable for most practical color applications involving relative measurements (e.g. CIELAB coordinates), but not for absolute measurements (e.g. tristimulus values or illuminance). Averge color inconstancy indices are lower than 0.6 CIE94 (1.0 CIELAB) color-difference units.
Research Interests:
Research Interests:
Research Interests:
ABSTRACT The grey scale method is commonly used for investigating differences in material appearance. Specifically, for testing color difference equations, perceived color differences between sample pairs are obtained by visually... more
ABSTRACT The grey scale method is commonly used for investigating differences in material appearance. Specifically, for testing color difference equations, perceived color differences between sample pairs are obtained by visually comparing to differences in a series of achromatic sample pairs. Two types of grey scales are known: linear and geometric. Their instrumental color differences vary linearly or geometrically (i.e., exponentially), respectively. Geometric grey scales are used in ISO standards and standard procedures of the textile industries. We compared both types of grey scale in a psychophysical study. Color patches were shown on a color-calibrated display. Ten observers assessed color differences in sample pairs, with color differences between ΔEab = 0.13 and 2.50. Assessments were scored by comparison to either a linear or a geometric grey scale, both consisting of six achromatic pairs. For the linear scale we used color differences ΔEab = 0.0, 0.6, 1.2,..., 3.0. For the geometric scale this was ΔEab=0.0, 0.4, 0.8, 1.6, 3.2, 6.4. Our results show that for the geometric scale, data from visual scores clutter at the low end of the scale and do not match the ΔEab range of the grey scale pairs. We explain why this happens, and why this is mathematically inevitable when studying small color differences with geometric grey scales. Our analysis explains why previous studies showed larger observer variability for geometric than for linear scales.
Research Interests:
Relationships between suprathreshold chroma tolerances and CIELAB hue‐angles have been analyzed through the results of a new pair‐comparison experiment and the experimental combined data set employed by CIE TC 1–47 for the development of... more
Relationships between suprathreshold chroma tolerances and CIELAB hue‐angles have been analyzed through the results of a new pair‐comparison experiment and the experimental combined data set employed by CIE TC 1–47 for the development of the latest CIE color‐difference formula, CIEDE2000. Chroma tolerances have been measured by 12 normal observers at 21 CRT‐generated color centers L*10 = 40, C*ab,10 = 20 and 40, and hab,10 at 30° regular steps). The results of this experiment lead to a chroma‐difference weighting function with hue‐angle dependence WCH, which is in good agreement with the one proposed by the LCD color‐difference formula [Color Res Appl 2001;26:369–375]. This WCH function is also consistent with the experimental results provided by the combined data set employed by CIE TC 1–47. For the whole CIE TC 1–47 data set, as well as for each one of its four independent subsets, the PF/3 performance factor [Color Res Appl 1999;24:331–343] was improved by adding to CIEDE2000 the WCH function proposed by LCD, or the one derived by us using the results of our current experiment together with the combined data set employed by CIE TC 1–47. Nevertheless, unfortunately, from the current data, this PF/3 improvement is small (and statistically nonsignificant): 0.3 for the 3657 pairs provided by CIE TC 1–47 combined data set and 1.6 for a subset of 590 chromatic pairs (C*ab,10&gt;5.0) with color differences lower than 5.0 CIELAB units and due mainly to chroma. © 2004 Wiley Periodicals, Inc. Col Res Appl, 29, 420–427, 2004; Published online in Wiley Interscience (www.interscience.wiley.com). DOI 10.1002/col.20057
Research Interests:
Research Interests:
Research Interests:
Random errors were propagated form tristimulus values to CIELAB and CIELUV color coordinates, using the instrumental color measurements of 28 Munsell samples illuminated by 3 light sources and performed by 3 different procedures. The... more
Random errors were propagated form tristimulus values to CIELAB and CIELUV color coordinates, using the instrumental color measurements of 28 Munsell samples illuminated by 3 light sources and performed by 3 different procedures. The errors found for the CIELAB and CIELUV color coordinates are considerably different for the 3 procedures. These errors are highest for the F source, and similar for TL84 and D65. Under our experimental conditions, we obtain that the instrumental errors for the a and b coordinates are lower than the visual subthresholds predicted by the CIE94 model.
Research Interests:
Research Interests:
Research Interests:
Research Interests:
—Texture, along with color, is one of the most important characteristics of a material defining the appearance of its surface. Different approaches to texture characterization can be considered. In this work texture is analyzed through... more
—Texture, along with color, is one of the most important characteristics of a material defining the appearance of its surface. Different approaches to texture characterization can be considered. In this work texture is analyzed through second order statistical measurements based on the Grey-Level Co-occurrence Matrix proposed by Haralick. By this method is possible to compute, among others, 5 features which are intended to describe texture: Contrast, Homogeneity, Dissimilarity, Energy and Entropy. The aim of this paper is to analyze the dependency of the features with the displacement considered for their computation and explore the possibility of features invariant under changes of the distance between the sample and observation position.
Research Interests:
... A comparison between illuminants and light-source simulators Rafael Roa(1,S), Rafael Huertas(1,S), Miguel Ángel López-Álvarez(2), Luis Gómez-Robledo(1) y Manuel Melgosa(1,*,S) ... [5] R. Huertas, R. Roa, MA López-Álvarez, L. Robledo... more
... A comparison between illuminants and light-source simulators Rafael Roa(1,S), Rafael Huertas(1,S), Miguel Ángel López-Álvarez(2), Luis Gómez-Robledo(1) y Manuel Melgosa(1,*,S) ... [5] R. Huertas, R. Roa, MA López-Álvarez, L. Robledo ... [6] R. Huertas, MJ Rivas, ...
RESUMEN A partir de los principales conceptos usados en la evaluación de diferencias de color, pretendemos dar al lector una información amplia y crítica sobre el estado actual de este campo de la Colorimetría. Consideraremos en... more
RESUMEN A partir de los principales conceptos usados en la evaluación de diferencias de color, pretendemos dar al lector una información amplia y crítica sobre el estado actual de este campo de la Colorimetría. Consideraremos en particular las últimas ...
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
International audienc
Research Interests:
Relating instrumental measurements to visually perceived colour-differences, under specific illuminating and viewing conditions, is one of the challenges of advanced colorimetry. Experimental data are used to devise new colour-difference... more
Relating instrumental measurements to visually perceived colour-differences, under specific illuminating and viewing conditions, is one of the challenges of advanced colorimetry. Experimental data are used to devise new colour-difference formulas as well as to assess the performance of other colour-difference formulas. In this paper, we analyse the consistency of experimental data employed at the development of the last CIE recommended colour-difference formula, CIEDE2000. Because of the subjective and imprecise nature of these data, we adopt a fuzzy approach, so that finally, for each experimental datum, we establish the fuzzy degree to which it can be considered consistent with the remaining data. The results of our analyses show that only a few data are associated with a rather low degree of consistency. These data in many cases correspond to colour pairs with a very small colour-difference for which visual assessments seem to be overestimated.
Research Interests:
Search: onr:"swepub:oai:services.scigloo.org:78536" > The Effect of Cultu... ... Ou, Li-Chen (author) Lou, Ronnier (author) Cui, G (author) show more... Woodcock, A (author) Billger, Monica, 1961-(author) Chalmers tekniska... more
Search: onr:"swepub:oai:services.scigloo.org:78536" > The Effect of Cultu... ... Ou, Li-Chen (author) Lou, Ronnier (author) Cui, G (author) show more... Woodcock, A (author) Billger, Monica, 1961-(author) Chalmers tekniska högskola, Institutionen för arkitektur Stahre, ...
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests: Chemical Engineering, Olive Oil, Color, Blue, Color Measurement, and 3 moreAzul, Bleu, and virgin olive oil
For calculating color differences, the CIEDE2000 and CIE94 equations are widely used and recommended. These equations were derived more than a decade ago, based for a large part on the RIT-Dupont set of visual data. This data was... more
For calculating color differences, the CIEDE2000 and CIE94 equations are widely used and recommended. These equations were derived more than a decade ago, based for a large part on the RIT-Dupont set of visual data. This data was collected from a series of psychophysical tests that use the method of constant stimuli. In this method, observers need to compare the color difference within a sample pair to that between a reference pair. In the current investigation, we show that the color difference equation significantly changes if reference pairs are chosen in the underlying visual experiments that differ from what was used when creating the RIT-Dupont dataset. The investigation is done using metallic paint samples representing two color centers, red and yellow-green. We show that the reproducibility differs for three different reference pairs, and that for modeling the visual data for the yellow-green color center, extra model terms are required as compared to the CIEDE2000 equation. Our results suggest that observers differ in their ability to mentally convert a color difference recognized in a sample pair into an equivalent color difference along the color difference direction represented by the reference pair. We also find that in these tests the tolerance to lightness differences is widened by a factor of 1.3 to 1.6, and that for the red color center the tolerance ellipsoid is rotated by 30° as compared to the CIEDE2000 equation. The latter observations are possibly due to the metallic texture in the samples used for the current experiment.