Evaluation of threshold color differences using printed samples

Spectral reflectance reconstruction based on wideband multi-illuminant imaging and a modified particle swarm optimization algorithm

A method for spectral reflectance factor reconstruction based on wideband multi-illuminant imaging was proposed, using a programmable LED lighting system and modified Bare Bones Particle Swarm Optimization algorithms. From a set of 16 LEDs with different spectral power distributions, nine light sources with correlated color temperatures in the range of 1924 K - 15746 K, most of them daylight simulators, were generated. Samples from three color charts (X-Rite ColorChecker Digital SG, SCOCIE ScoColor paint chart, and SCOCIE ScoColor textile chart), were captured by a color industrial camera under the nine light sources, and used in sequence as training and/or testing colors. The spectral reconstruction models achieved under multi-illuminant imaging were trained and tested using the canonical Bare Bones Particle Swarm Optimization and its proposed modifications, along with six additional and commonly used algorithms. The impacts of different illuminants, illuminant combinations, algorithms, and training colors on reconstruction accuracy were studied comprehensively. The results indicated that training colors covering larger regions of color space give more accurate reconstructions of spectral reflectance factors, and combinations of two illuminants with a large difference of correlated color temperature achieve more than twice the accuracy of that under a single illuminant. Specifically, the average reconstruction error by the method proposed in this paper for patches from two color charts under A + D90 light sources was 0.94 and 1.08 CIEDE2000 color difference units. The results of the experiment also confirmed that some reconstruction algorithms are unsuitable for predicting spectral reflectance factors from multi-illuminant images due to the complexity of optimization problems and insufficient accuracy. The proposed reconstruction method has many advantages, such as being simple in operation, with no requirement of prior knowledge, and easy to implement in non-contact color measurement and color reproduction devices.

Influences of shape, size, and gloss on the perceived color difference of 3D printed objects

In order to study the influence and mechanisms of color differences using 3D-shaped objects, 440 pairs of 3D samples surrounding five CIE color centers (gray, red, yellow, green, and blue) with the variations of gloss, size, and shape were prepared by a Sailner 3D color printer, and their color differences were assessed by 26∼45 observers using the gray-scale method. The new color difference data were used to investigate the parametric effects (gloss, 3D shape, and size) on the perceived color difference. Results indicate that, for 3D objects, high gloss and small size objects (2 cm) raise smaller visual color differences than matte and large size objects (4 cm), and the visual color difference of spheres is larger than that of the cone and cylinder sample pairs. The chromaticity ellipses indicated that the glossy samples with different shapes will arouse fairly different visual perceptions, especially for sphere and cylinder samples.

Preventing the Undesired Surface Veiling after Nanolime Treatments on Wall Paintings: Preliminary Investigations

During the last decades, the discovery of nanolime and its introduction in the field of Cultural Heritage has entailed a significant advance for the consolidation of historic wall paintings. Nevertheless, its use is not completely generalized yet within the conservation practitioner’s community due to its undesired white veiling deposit on the surface after treatment which usually covers the pictorial layer. Given the scarcity of existing literature which specify how to mitigate this undesired side-effect, the aim of this work is to carry out the first assessment of possible cleaning and treatment methods to eliminate those deposits and, at the same time, to analyse their effects on the consolidation properties. To do that, we have developed laboratory fresco wall paintings specimens. After applying an artificial ageing cycle to all of them, we consolidated them with CaloSil IP25, one of the most currently used commercial product in the practice. The elimination of the whitish deposits has been investigated with different methods: (1) wiping off the superficial excess of product immediately after each application during the treatment; (2) mechanical cleaning (scalpel) after consolidation; chemical cleaning with rigid gels of water (3), ethylenediaminetetraacetic acid (EDTA) (4) and citric acid (5) after consolidation. The effectiveness of each cleaning method has been assessed by non-destructive methods before and after the consolidation, and repeated after cleaning, by measuring differences in colour, water absorption by capillarity (i.e., sponge test), superficial adhesion (i.e., Scotch Tape Test) and by quantifying the thickness of the deposits eliminated by means of photogrammetry. Results show that both the mechanical cleaning and the removal of the excess of product after each application during the treatment yielded the most promising results for conservation practice.

Bayesian approach for developing threshold color-difference models by the strip-pair comparison method

A Bayesian approach alternative to the one used in the strip-pair comparison method for developing threshold color-difference models is presented in this paper. Strip-pair comparison method is based on the construction of color-control strips made of pairs of patches put in contact and ordered by increasing the CIELAB color difference. Observers are required to indicate the number of the pair of patches in every strip for which they begin to perceive a just noticeable color difference. Frequency data obtained, from repeating several times the visual assessment, is recorded to build a Bayesian multinomial logistic regression model, which allows the determination of the coefficients of the color discrimination ellipsoids. The results of the Bayesian approach agree closely with the results obtained to validate strip-pair comparison method for the same theoretical frequency data. The main advantage of the Bayesian approach over many other methods is that it allows a direct analysis of the statistical variability of the estimated parameters by means of confidence intervals and other measures of statistical variability.

Optimization of the method for color measurement and color-difference calculation of holographic prints with light pillars

To determine the methods of color measurement and color-difference calculation for holographic prints with light pillars, 94 pairs of holographic prints constituted by 17 different products were collected. A set of color-difference comparison experiments was organized by 64 observers with normal color vision, and a total of 86 groups of visual judgments were gathered. The CIELAB and CIEDE2000 color-difference values were calculated on the basis of the analysis of the microstructures of gratings distributed on the holographic paper. The performances of the original formulas were evaluated in terms of the standardized residual sum of squares index, and then they were optimized considering the power function effects (a, b factors) together with a contribution from lightness (k_L factor). Meanwhile, the color-difference threshold of the holographic prints was estimated with a goal to minimize the number of wrong decision in the visual experiment; therefore, the values were set as 2.50 and 2.00 for the original CIELAB and CIEDE2000 with the consistency of 91.5% and 98.9%, respectively. The results can also provide guidance to evaluate the color quality of the holographic prints with light pillars in the packaging and printing industries.

Goniochromatic assessment of gray scales for color change

The dependence of color differences on the illumination and viewing directions for two widely used gray scales for color change (SDCE and AATCC) was evaluated through measuring the spectral bidirectional reflectance distribution function (BRDF) by a gonio-spectrophotometer of metrological quality. Large incidence and viewing angles must be specially avoided using these gray scales because, in these conditions, color differences vary considerably from those established in ISO 105-A02 and ASTM D2616-12. While the visual appearance of the SDCE and AATCC gray scales for color change is similar, our results indicate that their goniochromatic properties are different. Finally, some recommendations regarding observation distance and illumination angle are given to correctly use these gray scales for visual experiments.

Parametric effects by using the strip-pair comparison method around red CIE color center

The strip comparison method, based on the serial exploration method described by Torgerson [Theory and Methods of Scaling; Wiley & Sons (1958); Chap. 7], for the development of near-threshold color difference models was presented and validated with theoretical data by the authors in a previous work. In this study, we investigate parametric effects derived from the use of the strip comparison method on chromaticity-discrimination ellipses around the red CIE color center. The results obtained led to the conclusion that the strip comparison method has little effect on the parameters of the chromaticity-discrimination ellipses determined by the pair comparison method when pairs of patches in the strips are separated by a black line 0.5 mm thick or are separated by 3 mm spacing on a white background and also correlates well with the parameters reported by other authors using the pair comparison method at the threshold.

Experimental method for measuring color appearance shifts in high-dynamic-range luminance conditions

We present an experimental method to determine color appearance shifts under high-dynamic-range conditions. A couple of light booths with variable luminance provide high-dynamic-range luminance conditions, and a perceptual color shift between the two booths is determined using color appearance matching. For red, green, yellow, and blue groups of four surface color samples, color shifts were measured for nine subjects under a dual illumination at background luminance levels of $100\,\,{{\rm cd/m}^2}$100cd/m² and $4700\,\,{{\rm cd/m}^2}$4700cd/m². We observed significant perceptual hue shifts toward blue with magnitudes of 2.5 to 3.9 and 5.0 to 6.9 CIELAB units, for the red and green samples, respectively, and decreases in chroma for most samples when changed from low to high luminances.

Parametric effects on the evaluation of threshold chromaticity differences using red printed samples

Results from different authors showed deviations of radial orientation in the a^*-b^* plane (tilt) for the major axes of chromaticity-discrimination ellipses centered around the International Commission on Illumination (CIE) red color center [Color Res. Appl.3, 149 (1978)CREADU0361-2317], which are not considered by most of the current advanced color-difference formulas (e.g., CIEDE2000). We performed a visual experiment using red printed samples in order to test the influence of the separation between samples (gap) on the mentioned tilt. Our results confirm a counterclockwise tilt of fitted a^*-b^* ellipses with a magnitude of approximately 36° for samples with no separation, which is similar to that detected by other authors, and a reduction of the mentioned tilt owing to the separation of the samples. We detected a tilt of approximately 22° for samples with a black gap of 0.5 mm and a tilt of approximately 25° for samples with a white gap of 3 mm. Notably, the uncertainty of previous values given by the corresponding credibility intervals of 95% posterior probability is approximately ±8° of the mean values. Finally, we study the performance of the most widely used color-difference formulas in the graphic arts sector using our current experimental results, and conclude that the performance of the CAM02-SCD and CAM02-UCS color-difference formulas is significantly better than that of the CIEDE2000 formula.

Colour differences in Caucasian and Oriental women's faces illuminated by white light-emitting diode sources

OBJECTIVE

To provide an approach to facial contrast, analysing CIELAB colour differences (ΔEab,10∗) and its components in women's faces from two different ethnic groups, illuminated by modern white light-emitting diodes (LEDs) or traditional illuminants recommended by the International Commission on Illumination (CIE).

METHODS

We performed spectrophotometric measurements of spectral reflectance factors on forehead and cheek of 87 young healthy women (50 Caucasians and 37 Orientals), plus five commercial red lipsticks. We considered a set of 10 white LED illuminants, representative of technologies currently available on the market, plus eight main illuminants currently recommended by the CIE, representative of conventional incandescent, daylight and fluorescent light sources. Under each of these 18 illuminants, we analysed the magnitude and components of ΔEab,10∗ between Caucasian and Oriental women (considering cheek and forehead), as well as for cheek-forehead and cheek-lipsticks in Caucasian and Oriental women. Colour-inconstancy indices for cheek, forehead and lipsticks were computed, assuming D65 and A as reference illuminants.

RESULTS

ΔEab,10∗ between forehead and cheek were quantitatively and qualitatively different in Orientals and Caucasians, but discrepancies with respect to average values for 18 illuminants were small (1.5% and 5.0% for Orientals and Caucasians, respectively). ΔEab,10∗ between Caucasians and Orientals were also quantitatively and qualitatively different both for forehead and cheek, and discrepancies with respect to average values were again small (1.0% and 3.9% for forehead and cheek, respectively). ΔEab,10∗ between lipsticks and cheek were at least two times higher than those between forehead and cheek. Regarding ΔEab,10∗ between lipsticks and cheeks, discrepancies with respect to average values were in the range 1.5-12.3%, although higher values of up to 54.2% were found for a white RGB LED. This white RGB LED provided the highest average colour-inconstancy indices: 17.1 and 11.5 CIELAB units, under reference illuminants D65 and A, respectively.

CONCLUSION

Colour contrasts in women's faces under CIE standard illuminants for outdoor and indoor conditions may be strongly altered using specific white LEDs. More research needs to be performed on the impact of spectral power distribution of light sources with high colour rendering indices on visual colour appearance of cosmetic products.

How psychophysical methods influence optimizations of color difference formulas

For developing color difference formulas, there are several choices to be made on the psychophysical method used for gathering visual (observer) data. We tested three different psychophysical methods: gray scales, constant stimuli, and two-alternative forced choice (2AFC). Our results show that when using gray scales or constant stimuli, assessments of color differences are biased toward lightness differences. This bias is particularly strong in LCD monitor experiments, and also present when using physical paint samples. No such bias is found when using 2AFC. In that case, however, observer responses are affected by other factors that are not accounted for by current color difference formulas. For accurate prediction of relative color differences, our results show, in agreement with other works, that modern color difference formulas do not perform well. We also investigated if the use of digital images as presented on LCD displays is a good alternative to using physical samples. Our results indicate that there are systematic differences between these two media.

Power functions improving the performance of color-difference formulas

Color-difference formulas modified by power functions provide results in better agreement with visually perceived color differences. Each of the modified color-difference formulas proposed here adds only one relevant parameter to the corresponding original color-difference formula. Results from 16 visual data sets and 11 color-difference formulas indicate that the modified formulas achieve an average decrease of 5.7 STRESS (Standardized Residual Sum of Squares) units with respect to the original formulas, signifying an improvement of 17.3%. In particular, for these 16 visual data sets, the average decrease for the current CIE/ISO recommended color-difference formula CIEDE2000 modified by an exponent 0.70 was 5.4 STRESS units (17.5%). The improvements of all modified color-difference formulas with respect to the original ones held for each of the 16 visual data sets and were statistically significant in most cases, particularly for all data sets with color differences close to the threshold. Results for 2 additional data sets with color pairs in the blue and black regions of the color space confirmed the usefulness of the proposed power functions. The main reason of the improvements found for the modified color-difference formulas with respect to the original color-difference formulas seems to be the compression provided by power functions.

Performance of select color-difference formulas in the blue region

The main objective of this work was to test the performance of major formulas for assessment of small suprathreshold color differences in the blue region. The models examined include CIELAB color space based equations, including CIELAB, CIE94, CIEDE2000, CMC (l:c), BFD (l:c), and formulas based on more uniform color spaces, such as DIN99d, CAM02-SCD, CAM02-UCS, OSA-GP, and OSA-Eu in comparison against data obtained via visual assessments. For this purpose, a dataset around the CIE high-chroma blue color center, hereafter called NCSU-B2, was developed. The NCSU-B2 dataset comprised 65 textile substrates and a standard, with a mean ΔE(ab)* color difference of 2.72, ranging from 0.54-5.72. Samples were visually assessed by 26 subjects against the reference gray scale in three separate trials with at least 24 h between assessments. A total of 5070 assessments were obtained. The standardized residual sum of squares (STRESS) index was used to examine the performance of various formulas for this dataset, as well as a previously developed NCSU-B1 low-chroma blue dataset [Color Res. Appl. 36, 27, 2011], and blue centers from other established visual datasets. Results show that formulas based on more recent uniform color spaces provide better agreement with perceptual data compared with models based on CIELAB space.

Measuring color differences in automotive samples with lightness flop: a test of the AUDI2000 color-difference formula

From a set of gonioapparent automotive samples from different manufacturers we selected 28 low-chroma color pairs with relatively small color differences predominantly in lightness. These color pairs were visually assessed with a gray scale at six different viewing angles by a panel of 10 observers. Using the Standardized Residual Sum of Squares (STRESS) index, the results of our visual experiment were tested against predictions made by 12 modern color-difference formulas. From a weighted STRESS index accounting for the uncertainty in visual assessments, the best prediction of our whole experiment was achieved using AUDI2000, CAM02-SCD, CAM02-UCS and OSA-GP-Euclidean color-difference formulas, which were no statistically significant different among them. A two-step optimization of the original AUDI2000 color-difference formula resulted in a modified AUDI2000 formula which performed both, significantly better than the original formula and below the experimental inter-observer variability. Nevertheless the proposal of a new revised AUDI2000 color-difference formula requires additional experimental data.

Color-difference evaluation for digital images using a categorical judgment method

The CIELAB lightness and chroma values of pixels in five of the eight ISO SCID natural images were modified to produce sample images. Pairs of images were displayed on a calibrated monitor and assessed by a panel of 12 observers with normal color vision using a categorical judgment method. The experimental results showed that assuming the lightness parametric factor k(L)=1 to predict color differences in images, CIELAB performed better than CIEDE2000, CIE94, or CMC, which is a different result to the one found in color-difference literature for homogeneous color pairs. However, observers perceived CIELAB lightness and chroma differences in images in different ways. To fit current experimental data, a specific methodology is proposed to optimize k(L) in the color-difference formulas CIELAB, CIEDE2000, CIE94, and CMC. From the standardized residual sum of squares (STRESS) index, it was found that the optimized formulas, CIEDE2000(2.3:1), CIE94(3.0:1), and CMC(3.4:1), performed significantly better than their corresponding original forms with lightness parametric factor k(L)=1. Specifically, CIEDE2000(2.3:1) performed the best, with a satisfactory average STRESS value of 25.8, which is very similar to the 27.5 value that was found from the CIEDE2000(1:1) formula for the combined weighted dataset of homogeneous color samples employed at the development of this formula [J. Opt. Soc. Am. A25, 1828 (2008), Table 2]. However, fitting our experimental data, none of the four optimized formulas CIELAB(1.5:1), CIEDE2000(2.3:1), CIE94(3.0:1), and CMC(3.4:1) is significantly better than the others. Current results roughly agree with the recent CIE recommendation that color difference in images can be predicted by simply adopting a lightness parametric factor k(L)=2 in CIELAB or CIEDE2000 [CIE Publication 199:2011]. It was also found that the different contents of the five images have considerable influence on the performance of the tested color-difference formulas.