Color Difference Formula Research Articles

Colour stability of 3D-Printed orthodontic brackets using filled resins.

To determine the effect of common beverages and accelerated aging on the colour stability of filled resins, which could potentially be used for fabrication of 3D-printed orthodontic brackets. GR-17.1 (shades A1, A2, and A3), and GR-10 Guide resins (pro3dure medical, Eden Prairie, MN) were printed on an Asiga MAX UV printer into discs 2 mm thick, with a diameter of 10 mm, and then post-print processed as per manufacturer's instructions. Discs were immersed in 5 mL of coffee, tea, red wine, or distilled water for 7 days. Another group was subjected to accelerated aging in accordance with ISO Standard 4892-2. Ten samples were produced per resin, per treatment condition. Colour measurements were taken on the discs before and after treatment using a spectrophotometer against white and black reference tiles to assess colour and translucency differences with the CIEDE2000 colour difference formula. While initial colour of the printed resin discs was acceptable, all resin groups underwent significant colour change during the experiment. Red wine and coffee produced the greatest colour and translucency change, followed by tea, with accelerated aging producing the least change in colour and translucency. The 3D-printed resins tested underwent significant changes in colour and translucency following exposure to endogenous and exogenous sources of staining, which may affect their acceptability for fabrication of aesthetic orthodontic brackets.

In-vitro evaluation of the effectiveness of polyphenols based strawberry extracts for dental bleaching

To formulate a dental bleaching agent with strawberry extract that has potent bleaching properties and antimicrobial efficacy. Enamel specimens (3 × 3 × 2 mm3) were prepared. Quaternary Ammonium Silane (CaC2 enriched) was homogenized with fresh strawberries: Group 1: supernatant strawberry (10 g) extract < Group 2: supernatant strawberry (10 g) extract + 15%HA (Hydroxyapatite) < Group 3: supernatant strawberry (10 g) extract + 15% (HA-2%k21) < Group 4: supernatant strawberry (20 g) extract only (20 g strawberries) < Group 5: supernatant strawberry (20 g) extract + 15% HA < Group 6: supernatant strawberry (20 g) extract + 15% (HA-2%K21) < Group 7: In-office Opalescence Boost 35%. Single-colony lactobacillus was examined using confocal microscopy identifying bacterial growth and inhibition in presence of bleaching agents using 300 µL aliquot of each bacterial culture. Images were analysed by illuminating with a 488 nm argon/helium laser beam. Colour difference (∆E00) was calculated using an Excel spreadsheet implementation of the CIEDE2000 colour difference formula and colour change measured between after staining and after bleaching. Scanning electron microscope was used to image specimens. Raman spectra were collected, and enamel slices were used for STEM/TEM analysis. HPLC was used for strawberry extract analysis. Nano-indentation was performed and X-ray photoelectron spectroscopy. Antioxidant activity was determined along with molecular simulation. hDPSCs were expanded for Alamar Blue Analysis and SEM. Mean colour change was significantly reduced in group 1 compared to other groups (p < 0.05). CLSM showed detrimental effects of different strawberry extracts on bioflms, especially with antimicrobial (p < 0.05). Groups 1, 2 and 3 showed flatter/irregular surfaces with condensation of anti-microbial in group 3. In strawberry specimens, bands predominate at 960 cm−1. HPLC determined the strawberry extracts content. Molecular simulation verified interaction between calcium and polyphenol components. XPS peak-fitted high-resolution corresponding results of Ca2p3/2 and Ca2p1/2 for all k21 groups. Combination of 10 g strawberry extract supernatant and 15% (hydroxyapatite 2%k21) improved the whiteness and provided additional antimicrobial potential. The novel strawberry extract and antimicrobial based dental formulation had immediate bleaching effect without promoting significant changes in enamel morphology.

Development of Thickness-Dependent Predictive Methods for the Estimation of the CIEL*a*b* Color Coordinates of Monolithic and Layered Dental Resin Composites.

Usually, dentin and enamel shades are layered in dental restorations with the purpose of mimicking the natural appearance of teeth. The main objective of this study was to develop and assess accuracy of a color-prediction method for both monolithic and layered dental resin-based composites with varying shades and under different illuminants. A total of 15 different shades of VITAPAN Excell, VITAPAN Dentine and VITA Physiodens as well as VITA Enamel of five different thicknesses (0.5-2.5 mm range) were used to manufacture monolithic and layered samples. A non-contact spectroradiometer with CIE 45∘/0∘ geometry was used to measure the color of all samples over a standard ceramic black background. Second-degree polynomial regression was used as predictive method for CIE-L*a*b* color coordinates. Performance of predictive models was tested using the CIEDE2000 total color difference formula (ΔE00), while accuracy was evaluated by comparative assessment of ΔE00 with corresponding 50:50% acceptability (AT00) and perceptibly (PT00) thresholds for dentistry. A mean color difference between measured (real) and predicted color of ΔE00=1.71, with 62.86% of the color differences below AT00 and 28.57% below PT00, was registered for monolithic samples. For bi-layered samples, the mean color difference was roughly ΔE00=0.50, with generally 100% and more than 85% of the estimations below AT00 and PT00, respectively. The predictive method allowed highly accurate color estimations for both monolithic and layered dental resin-based composites with varying thicknesses and under different illuminations. These results could be useful to maximize the clinical success of dental restorations.

Optimizing Color-Difference Formulas for 3D-Printed Objects.

Based on previous visual assessments of 440 color pairs of 3D-printed samples, we tested the performance of eight color-difference formulas (CIELAB, CIEDE2000, CAM02-LCD, CAM02-SCD, CAM02-UCS, CAM16-LCD, CAM16-SCD, and CAM16-UCS) using the standardized residual sum of squares (STRESS) index. For the whole set of 440 color pairs, the introduction of kL (lightness parametric factor), b (exponent in total color difference), and kL + b produced an average STRESS decrease of 2.6%, 26.9%, and 29.6%, respectively. In most cases, the CIELAB formula was significantly worse statistically than the remaining seven formulas, for which no statistically significant differences were found. Therefore, based on visual results using 3D-object colors with the specific shape, size, gloss, and magnitude of color differences considered here, we concluded that the CIEDE2000, CAM02-, and CAM16-based formulas were equivalent and thus cannot recommend only one of them. Disregarding CIELAB, the average STRESS decreases in the kL + b-optimized formulas from changes in each one of the four analyzed parametric factors were not statistically significant and had the following values: 6.2 units changing from color pairs with less to more than 5.0 CIELAB units; 2.9 units changing the shape of the samples (lowest STRESS values for cylinders); 0.7 units changing from nearly-matte to high-gloss samples; and 0.5 units changing from 4 cm to 2 cm samples.

Testing the Performance of Color Difference Formula for a Mixed Display Technology Setup

Automotive cockpits are becoming more and more digital day by day and this is evident by the increase in the number of displays inside the cockpit. With the advent of OLED displays, automotive cockpits not only have LCD but have started having mixed display technologies. A recent example of such a cockpit display is the MBUX Hyperscreen in Mercedes EQS. A general situation is most mid ranged cars from Renault includes several displays inside the cockpit. These displays are placed at different locations inside the cockpit and go through various changes in external environmental condition during day and night. A vehicle cockpit experiences a wide range of illumination change during the day, from 35 kLux in bright sunlight to a few Lux during the night. The displays are generally used in high luminance range during the day and very low luminance during the night. Traditional color difference formulae like the CIEDE76 or CIEDE2000, the latter being the current industry standard, are defined for a specific set of evaluation conditions. For the myriad of different conditions that the displays undergo inside the cockpit, there isn&#x2019;t a recommended color difference formula which can be used to quantify the color difference between any two chosen displays inside the cockpit. An attempt has been made to include various real time parameters involving color difference evaluation between two displays, one of which is an LCD and other OLED. The motive of this study is to find out which color difference formula is the most representative of the perceived color difference between two mixed technology displays for a group of observers. The metric used for this the study is the CIE recommended STRESS index. The outcome of this research is to serve as a reference regarding the choice of color difference metric by display manufactures and OEM suppliers.

The impact of remineralization agents on dental bleaching efficacy and mineral loss in bleached enamel.

This study evaluated the effect of remineralization agents on bleaching efficiency, enamel mineral changes, and post-bleaching color stability. A total of 112 enamel-dentin blocks were prepared from bovine teeth. Following initial color measurements, separate treatment regimens were carried out as follows: negative control (no treatment); positive control (bleaching only); bleaching, then NaF; bleaching + NaF (mix); bleaching, then CPP-ACPF; bleaching + CPP-ACPF (mix); bleaching, then nHAP+F; bleaching + nHAP+F (mix). Color measurements were repeated after immersion in distilled water for 7 days, and again after staining with coffee solution for 14 days. The CIELAB-based whiteness index was used to evaluate bleaching efficiency, and the CIEDE2000 color difference formula for color stability. Chemical investigation was performed using scanning electron microscopy with energy dispersive spectroscopy and X-ray diffraction analyses. The experimental groups showed significant increases in whiteness compared to the negative control, and the staining after bleaching did not result in statistically significant differences between the groups. Energy dispersive spectroscopic analysis revealed that bleaching protocols had no impact on elemental levels as well as the ratio of Ca/P. The combined use of bleaching agents with remineralization agents did not affect bleaching effectiveness but also did not provide an additional contribution.

Parametric effects in color-difference evaluation.

An experiment was conducted to investigate three parameters affecting color-difference evaluation on a display: 4 sample sizes (2°, 4°, 10°, and 20°), 2 color-difference magnitudes (4 and 8 CIELAB units), and 2 separations (inclusion or exclusion of the separation line between two colors in a pair). Sample pairs surrounding 5 CIE recommended color centers were prepared. In total, 1120 sample pairs of colors were assessed 20 times using the grey-scale method. The experimental results were used to reveal various parametric effects and to verify the performance of different color matching functions (CMFs) and four color difference formulae and uniform color spaces. It was found that there was little difference in terms of ΔE values calculated using different CMFs for all the color models tested. A parametric formula was proposed to predict three parametric effects for sample pairs having no-separation line: 1) differences in sample size, 2) media (surface and self-luminous colors), and 3) color-difference magnitudes.

Color Change Evaluation of Three Universal Resin Composites after Storage in Water: An In Vitro Study

Aim: The aim of this in vitro study was to evaluate the color changes of three different universal resin composites after immersion in distilled water for one month. Materials and Methods: Omnichroma, Estelite Σ Quick, and Filtek Universal Restorative were investigated. Ten disk shaped specimens (6 mm diameter, 2 mm thickness) were prepared according to the manufacturers’ instructions for each material. After polishing, initial color measurements were taken followed by individual storage of the specimens in distilled water at 37 °C for one month when color measurements were repeated. The change in the color of each resin composites (Δ E00) was calculated with a digital method, using the CIEDE2000 color difference formula. The data were analyzed using one-way ANOVA followed by Tukey post-hoc test ( P &lt; .05). Results: All resin composites exhibited acceptable color change after one month. Omnichroma exhibited the highest color change (2.26 ± 0.48) value while Filtek Universal Restorative showed the lowest (1.14 ± 0.38) value. All color parameters influenced the Δ E00 values in all groups except Filtek Universal for Δ L* and Δ b values. Conclusion: When performing composite resin restorations, especially for esthetic purposes, polymerization may lead to change in the color of restorative material over time, but it should be considered whether this is within acceptable limits.

Metrics of color-difference formula improvement.

Metrics of color-difference formula improvement (i.e., standardized residual sum of squares and Pearson product moment correlation) are shown to convey the same information. Furthermore, each metric has two computational forms that assume different linear data models, specifically, with or without an ordinate intercept. It is essential to choose a computational form that matches the data model. We recommend explicitly declaring whether or not the data have been centered, i.e., by subtracting the mean value from each datum, to match the intercept-free data model. Statistical testing of the metrics assumes independent, normally distributed randomness of residuals from the data model, and homogeneous variance. Procedures consistent with these assumptions include robust statistical tests, homogenizing data transformations, and meta-analysis.

Colour Difference Formula for Photopic and Mesopic Vision Incorporating Cone and Rod Responses

The standard colour difference formulas, such as CIEDE2000, operate on colours defined by cone-fundamentals, which ignore the influence of rods on colour perception. In this work, we combine the rod intrusion model by Cao et al. with the popular CIEDE2000 colour difference formula and validate the accuracy of the new formula on three contrast sensitivity datasets. When compared with the standard CIEDE2000 formula, the new colour difference formula improves the perceptual uniformity of the space at low luminance levels.

Color difference of yarn-dyed fabrics woven from warp and weft yarns in different color depths

PurposeThis paper aims to determine the most practically applicable color-difference formula for yarn-dyed fabrics woven from warp and weft yarns in different color depths and to establish color-difference tolerance for perceptibility by evaluating yarn-dyed fabrics visually and instrumentally.Design/methodology/approachA total of 108 sample pairs were evaluated by a panel of 13 observers with perceptibility method under three typical light sources (A, D65 and cool white fluorescent). The data sets were statistically analyzed by the homogeneity of variance test (F-test), analysis of variance, standardized residual sum of squares and performance factor/3.FindingsLight sources had a slight influence on the visual assessments of yarn-dyed fabrics. Among the eight color-difference formulae for measurements of yarn-dyed fabrics, CIEDE2000(2:1:1) outperformed all other tested formulae, and the color tolerance for the perceptibility of CIEDE2000(2:1:1) was 0.62. When the homochromy index (K) of warp and weft yarns of yarn-dyed fabric was lower than 1.25, the color difference based on ΔE*00(2:1:1) between the two samples was acceptable in terms of the color tolerance for perceptibility (i.e. 0.62).Practical implicationsThe warp and weft yarns in different color depths could be woven in fabric with a relatively uniform color appearance.Originality/valueThis study could contribute to cost savings by reusing disqualified dyed yarns during the weaving manufacturing process.

Optimizing Parametric Factors in CIELAB and CIEDE2000 Color-Difference Formulas for 3D-Printed Spherical Objects.

The current color-difference formulas were developed based on 2D samples and there is no standard guidance for the color-difference evaluation of 3D objects. The aim of this study was to test and optimize the CIELAB and CIEDE2000 color-difference formulas by using 42 pairs of 3D-printed spherical samples in Experiment I and 40 sample pairs in Experiment II. Fifteen human observers with normal color vision were invited to attend the visual experiments under simulated D65 illumination and assess the color differences of the 82 pairs of 3D spherical samples using the gray-scale method. The performances of the CIELAB and CIEDE2000 formulas were quantified by the STRESS index and F-test with respect to the collected visual results and three different optimization methods were performed on the original color-difference formulas by using the data from the 42 sample pairs in Experiment I. It was found that the optimum parametric factors for CIELAB were = 1.4 and = 1.9, whereas for CIEDE2000, = 1.5. The visual data of the 40 sample pairs in Experiment II were used to test the performance of the optimized formulas and the STRESS values obtained for CIELAB/CIEDE2000 were 32.8/32.9 for the original formulas and 25.3/25.4 for the optimized formulas. The F-test results indicated that a significant improvement was achieved using the proposed optimization of the parametric factors applied to both color-difference formulas for 3D-printed spherical samples.

47‐4: Color Acceptability Threshold for Mixed Display Technology Automotive Cockpit

The number of displays inside an automotive cockpit is increasing, and so is the possibility to tap into new technologies. CuJTently, LCD displays are used in most of the mid to high price range cars, but OLED displays have also started making their appearance in cars like Audi E‐Tron, Cadillac Escalate, Mercedes EQS etc. There can be scenarios where the cockpit might have displays with mixed technologies, for example, one display can be an LCD and the other can be an OLED. In this paper we have evaluated the color difference acceptability threshold for such a mixed technology scenario (an LCD and an OLED). A detailed workflow to study the acceptability of users from different age groups through a psychophysical experiment is designed and documented. The acceptability threshold is published using the major color difference formulae available in literature, i.e., CIEDE2000, CIEDE76, CIECAM02‐UCS, DI99d, OSA‐GP and CAMI6‐UCS. This study acts as the first pilot study in the series of studies where several other factors affecting this acceptability threshold will be studied.

Does Backgrounds Color Influence the Appearance of Gingiva-Colored Resin-Based Composites?

Dental materials are mainly tested in vitro, so laboratory conditions must reproduce the oral environment to ensure the validity of their results. This study aimed to evaluate the influence of backgrounds on the color of gingiva-colored resin-based composites (GCRBC). Three discs of each of 20 shades of GCRBCs and each thickness (1 and 2 mm) were prepared. Diffuse reflectance was measured on-air and over three natural teeth (0M3/B1, 3M3/B3, and 5M3/B4 shades of Vita 3D Master/Vita Classical guides, respectively) using a calibrated spectroradiometer, CIE D65 illuminant and the CIE 45°/0° geometry. CIEDE2000 color difference formula and its 50:50% perceptibility and acceptability thresholds have been used to calculate and interpret the results. It can be stated that the background influences the color of all GCRBCs tested, although the effect is more pronounced for 1 mm thick samples. L*, a* and b* coordinates values of GCRBCs on air were significantly different from those obtained on natural teeth backgrounds, and the total color differences were greater than the acceptability thresholds. Since GCRBCs are placed on a dental substrate in clinical conditions, it is not advisable to perform color measurements of GCRBCs on-air because of the high color differences found. This recommendation is especially relevant for thin specimens.

Computer Artificial Intelligence Technology in the Visual Transmission System of Urban Lake Water Quality Inspection and Detection Images

Purpose. Based on artificial intelligence technology, this paper uses the real-time data measured in the monitoring waters and the minimum value of the inversion result map to analyze the logarithmic function relationship. Methods. Multitarget tracking algorithm was used to detect lake water quality. A spectral colour difference formula for detecting heavy metal ions in lake water is proposed. Results. The research results show that the content of metal ions in water must be detected, and the research method used in this paper is very meaningful. Conclusion. The detection method proposed in this paper can improve the detection speed of lake water pollution.

Masking Ability of Monolithic and Layered Zirconia Crowns on Discolored Substrates.

There is scarce information on the colorimetric behavior of monolithic and layered zirconia crowns in combination with various abutment colors. This study evaluated the masking ability on discolored substrates of monolithic and layered zirconia crowns. Anterior crowns were fabricated using 3Y-TZP zirconia and layering ceramic and divided into three groups: monolithic (ML), bi-layer (BL), and tri-layer (TL). The crowns were placed over eleven substrates (ND1-ND9, zirconia, metal), and CIE L*, a*, b*, C*, and h° color coordinates were measured in the cervical, middle, and incisal areas with a spectrophotometer. Masking ability was calculated using the color difference formula, and values were interpreted according to the perceptibility and acceptability thresholds. Data were analyzed statistically (α = 0.001). The L* coordinate was not significantly different between BL and TL crowns, regardless of the measurement area or substrate (p ≥ 0.001). In the middle area, the L* coordinate of the ML group was statistically different from the BL and TL groups only for zirconia and metal substrates, while in the incisal area, only for ND7 and metal substrates. The a* coordinate was significantly different between the ML and layered crowns for all measurement areas and substrates (except zirconia). The b* and C* coordinates differed significantly between the groups only in the cervical area (p < 0.001). The ML crown had better masking ability than the BL and TL crowns. However, the color differences for ML crowns were below the acceptability threshold for ND2, ND3, and ND7 substrates in the cervical and middle areas and below perceptibility threshold only for the incisal area. The lowest masking ability of the crowns was found for ND9 and metal substrates in all measurement areas.

COLOR PERCEPTION ESTIMATIONS OF METAMERIC PAIRS UNDER DIFFERENT ILLUMINANCE LEVELS

LEDs or light emitting diodes of the lighting class dominate both the indoor and outdoor lighting industries today due to their accuracy and consumer-friendly color temperature. In the context of color science, it is necessary to analyze both the spectral power distribution of lighting and the human characteristics of color perception under these lights. In this article, we provide estimates of the appearance of eleven metameric pairs under LEDs with four correlated color temperatures and six illuminance levels, using color difference formulas based on the CIELAB, CAM02-UCS, and CAM16-UCS models to verify our estimates. We followed ASTM D4086 standard visual methods for detecting metamerism and for estimating the magnitude of a metameric color difference. Our investigations found that color appearance models are more reliable than CIELAB in evaluating color difference under various LED conditions. CAM16-UCS more accurately predicted the color difference estimates between all three formulas. Our comparative study confirms that the variation in the estimates with the CCT and illuminance levels of the LED sources depends on the color appearance model used. The results also showed that in order to determine the color difference of metameric pairs, optimal conditions regarding the colorimetric properties of the samples and the variability of the observer should be considered separately. We noticed an increasing correlation trend with increasing illuminance. However, there was no such increase or decrease trend in CCTs. The trend of the STRESS change in the color appearance models showed the influence of the chromatic adaptation, but the establishment of adaptation patterns is far beyond the scope of this work. Although our research has had limitations on correlated color temperature and illuminance, we believe that it can be beneficial for the lighting application to ensure correct lighting decisions when assessing the color differences of metameric pairs.

Color and translucency of enamel in vital maxillary central incisors

Statement of problemLimited data, especially in vivo data, exist regarding translucency parameter (TP) values for vital anterior nonrestored dentition. Additionally, published information on the CIELab values of vital enamel at a theoretical infinite thickness is lacking. Obtaining TP and CIELab values in a population that varies in terms of ethnicity, age, and sex would be useful to inform the development and placement of esthetic dental restorations that more accurately capture the complex optical qualities of enamel. PurposeThe purpose of this clinical study was to investigate in vivo the TP and CIELab values of vital anterior incisor enamel at a theoretical infinite thickness in a diverse pool of participants who varied in age, ethnicity, and sex. Material and methodsSpectral reflectance measurements (380 to 780 nm at 2-nm intervals) of the mid-incisal region of vital, unrestored maxillary anterior teeth were made in 120 participants, equally divided into 2 sexes, 4 racial or ethnic groups, and 5 age ranges. Instruments were oriented to achieve 0-degree observation and 45-degree illumination, and spectral measurements were made with white and black silicone backgrounds. Reflectance spectra of the incisal enamel from both the black and white silicone backing were used to fit to the Kubelka-Munk (K-M) reflectance theory. The CIEDE2000 color difference formula was used to determine TP, and data were compared among participant demographics. CIELab color coordinate values for enamel at an infinite thickness were calculated by using a D65 illumination and CIE standard human (2-degree) observer. To determine value ranges and significant differences among participant groups, CIELab values were analyzed with a 4-way ANOVA, and TP values were analyzed with a generalized linear mixed model. Pairwise comparisons of interest were evaluated with Bonferroni-corrected Student t tests. ResultsFor maxillary central incisor enamel, the average TP was 10.1 ±3.6, and the average CIELab color coordinates were L∗=73.5 ±7.6, a∗=2.2 ±1.8, b∗=11.9 ±8.4. TP values of incisal enamel significantly differed among specific age and ethnic groups, with general significant interactions of age and sex (P=.009), as well as ethnicity and age (P=.042). CIE color coordinates of enamel at an infinite thickness were found in the L∗ coordinate among different age groups with the same sex and ethnicity, specifically when comparing CIELab direction with the population characteristics of age (P=.011) and the interaction between age, sex, and ethnicity (P=.035). ConclusionsIn vivo L∗ values and TP values of incisal enamel differed significantly among groups determined by ethnicity, age, and sex.

Comparison of visual shade matching and photographic shade analysis.

To compare the performance of a standardized photographic shade analysis (PSA) and visual shade matching (VSM) using two color difference formulas. Fifty observers (35 undergraduate and 15 graduate students) evaluated the color of two upper left central incisors (LT-light tooth, and DT-dark tooth). VSM was performed using the VITA 3D Master (3D) shade guide in a controlled clinical environment. For PSA, a cross-polarized filter and a gray card (Whibal) were used to standardize the photographs taken (target teeth and shade tabs from 3D). From the pictures obtained, the CIELAB coordinates, and color differences ( and ΔE00 ) were obtained. The shade tabs selected by two experienced researchers were conducted as part of the pilot study, and finally used as a standard for the analysis. Data were analyzed using descriptive statistics and the chi-square test (p ≤ 0.05). Shade tabs selections of VSM and PSA agreed only for LT. The best "Match" selected by the researchers agreed with data from PSA using ΔE00 . PSA using ΔE00 showed higher total percentages of "Match" and higher percentage of agreement among observers. A relationship was found for LT performing the PSA (p < 0.05). The performance of the PSA was better than the VSM, but only when the CIEDE2000 color difference formula was used. Therefore, the color difference formulas influenced on the performance of PSA. Finally, the PSA improved the precision of the VSM. To use a standardized PSA to improve the VSM and shade communication in clinical esthetic dentistry.

Similarity between two color areas

The paper introduces a method to compare two areas of colors, with each area presenting a perceptual single major color such as on a piece of cloth or a piece of tile. Each color area contains a cloud of colors in similar hues and all colors present a scattered distribution in the RGB color cube. Existing color difference formulas comparing two single colors do not work well in this case. The new method presented in the paper includes two aspects, a new color model that better describes color distributions and the technique of comparing two areas of colors by their color distributions under the new color model. The new model uses cylindrical coordinates to describe the color features, and an area of colors shows a distribution pattern on each color feature. For two areas of colors that are perceptually similar, their distributions on each component of the new color model are compared for similarity, and a combination of these sub-similarities gives an overall similarity between the two areas of colors. The proposed method can be applied to many industrial processes where color similarity comparison is a main concern such as color fastness test of fabrics and tile classification by color.