Color Difference Formula Research Articles

Color Ranges and Distribution of Human Teeth: A Prospective Clinical Study.

This study investigated the in vivo color range of human teeth using a research-grade noncontact spectroradiometer, analyzing the effects of gender, age, ethnicity, and lifestyle factors, including diet, smoking, and oral hygiene. A total of 1004 participants were recruited at two research sites and stratified by gender, age, and ethnicity, and data on their dietary and oral habits were collected. Noninvasive color measurements of an upper central incisor were performed using a spectroradiometer and a fiber-coupled Xe-Arc light source. Color differences were computed using the CIELAB and CIEDE2000 color difference formulas, statistically analyzed, and interpreted through comparisons with 50:50% perceptibility (PT) and acceptability (AT) thresholds for dentistry. CIELAB and CIEDE2000 color coordinate values varied significantly. Female teeth appeared lighter and less yellow than men's. Age correlated with darker, more chromatic teeth, stabilizing only after Age 46. Significant ethnic differences were observed, particularly between African-American and Asian participants. Coffee consumption impacted teeth yellowness and chromaticity, while tea had no significant effect. Frequent tooth brushing led to lighter teeth, and tooth whitening considerably influenced color, emphasizing the effect of cosmetic dental treatments. Smoking showed minimal impact, with slight discoloration noted among light smokers compared to nonsmokers. Color coordinate values by gender, age, and ethnicity exhibited statistically significant differences and, in most cases, noticeable color differences. With exceptions, the dietary/oral habits of the patient had a significant impact on the color of human teeth. The findings from this study provide detailed information and understanding of the color range and distribution of human teeth, which can help enhance the esthetic outcome of dental care and, consequently, the patient's satisfaction.

Leveraging multi-output modelling for CIELAB using colour difference formula towards sustainable textile dyeing

Textile dyeing requires optimizing combinations of ingredients and process parameters to achieve target colour properties. Modelling the complex relationships between these factors and the resulting colour is challenging. In this case, a physics-informed approach for multi-output regression to model CIELAB colour values from dyeing ingredient and process inputs is proposed. Leveraging attention mechanisms and multi-task learning, the model outperforms baseline methods at predicting multiple colour outputs jointly. Specifically, the Transformer model’s attention mechanism captures the complex interactions between dyeing ingredients and process parameters, while the multi-task learning framework exploits the intrinsic correlations among the L*, a*, and b* dimensions of the CIELAB colour space. In addition, the incorporation of physical knowledge through a physics-informed loss function integrates the CMC colour difference formula. This loss function, along with the attention mechanisms, enables the model to learn the nuanced relationships between the dyeing process variables and the final colour output, thereby improving the overall prediction accuracy. This reduces trial-and-error costs and resource waste, contributing to environmental sustainability by minimizing water and energy consumption and chemical emissions.

In Vitro Effect of Anodization of Titanium Abutments on Color Parameters and Color Difference of Lithium Disilicate All-Ceramic Crowns.

This study assessed the effect of the anodization of titanium abutments on the color parameters and color difference of lithium disilicate (LDS) all-ceramic crowns. In this study, 19 straight abutments were divided into two groups: anodized (n = 9) and non-anodized control (n = 9), with one hybrid zirconia abutment as a reference. Anodization was achieved by applying 63 V energy using seven 9 V flat batteries in series, with an electrolyte solution comprising 1 g trisodium phosphate in 250 mL distilled water for 5 s, resulting in a gold-yellow color. Abutments were then scanned, and full-contour monolithic IPS e.max maxillary central incisor crowns were fabricated with 2 mm thickness and glazed. Reflectance was measured using a spectroradiometer, and color coordinates (L*, a*, b*, h*, and C*) were calculated using CS-10W software. Color differences of the crowns in both groups were quantified using the CIEDE2000 (ΔE00) color difference formula and analyzed by t-test (α = 0.05) compared to the standard sample. The L*, a*, b*, and c* parameters in anodized abutments were significantly higher than those in non-anodized abutments, while the h* parameter in anodized abutments was significantly lower than that in non-anodized abutments (p < 0.001 for all). There was a significant difference in ΔE00 of the two groups (p = 0.043). Anodization of titanium abutments improved the color parameters of LDS all-ceramic crowns and significantly decreased their ΔE compared with non-anodized abutments.

Colour difference detection algorithm for warp‐knitted fabric based on image colour appearance model

AbstractDetecting colour differences in warp‐knitting fabric is essential to ensure its quality. Machine vision algorithms are commonly used for automatic colour difference detection. However, the current algorithm directly extracts RGB (red, green, blue) colour stimulus values from the image without considering the image's colour attributes, leading to a significant error in colour difference detection. To solve this issue, a colour appearance model is introduced into the field of colour difference detection for warp‐knitted fabric. Initially, a colour appearance model based on CAM16 is established, and the critical parameters are calculated to obtain the colour appearance attribute of the fabric. The colour difference calculation formula is then constructed in the uniform colour space of CAM16‐UCS. A template selection algorithm based on principal component analysis was designed to select warp‐knitted cloth images with standard colours. Subsequently, a cloth colour difference detection algorithm was developed using the cloth colour profile model. The performance of the colour difference formula based on the colour profile model was evaluated using the PF/3 method. To compare the CIELab, CMC(2:1), and CIEDE2000 colour difference formulas, standardised residual sum of squares was used. The results indicated that the colour difference formula based on the colour‐appearance model is about 5.32% different from the visual colour difference perceived by the human eye. However, it can perform as well as the CMC(2:1) colour difference formula, which is widely used in the textile industry.

Instrumental and Visual Evaluation of the Chameleon Effect of Single-shaded Composite Resins.

To evaluate the shade-matching ability of single-shade resin-based composite restorations in different thicknesses using both instrumental and visual techniques. Cavities with 4 mm diameter and 2 mm (n=96) or 3 mm (n=96) depth were prepared in acrylic incisor teeth of shades A2, A3, B3, and C2 and restored with three single-shade resin composites, Omnichroma (Tokuyama Dental America, Encinitas, CA, USA [OM]), Vittra APS Unique (FGM Dental Group, Joinville, SC, Brazil [VU]), Zenchroma (President Dental, Allershausen, Germany [ZC]), and a microhybrid resin composite (Filtek 3M Z250 3M ESPE, St Paul, MN, USA [FZ]) of A2, A3, B3, and C2 shades. Readings were obtained using VITA Easyshade V spectrophotometer for the teeth and restorations. The CIEDE2000 (ΔE00) color difference formula was used, and the values were assessed using three-way analysis of variance (ANOVA). Forty-eight evaluators graded the shade match of 32 different specimens visually as (A) best shade match, (B) intermediate shade match, and (C) poor shade match. FZ material achieved satisfactory matches for both thicknesses, across all shades, and OM material demonstrated statistically significant lower shade matches than the ZC and the FZ materials (p<0.05). VU exhibited poor shade match with the highest ΔE00 value on C2 shade. According to the visual examination, the best shade matches were observed for FZ on A3-shade and ZC on C2-shade teeth. Shade matching for 2 mm and 3 mm-thick composite resin restorations is material- and tooth-shade dependent.

Analyzing the effect of blue-blocking lenses on color vision tests using the chromaticity coordinate method

SignificanceBlue light with wavelengths of 380–445 nm can harm the retina, leading to the development of blue-blocking lenses (BBLs). Understanding whether BBLs affect color vision test outcomes and color discrimination ability is crucial for people in color-associated jobs. AimThis study aimed to evaluate the effect of BBLs on color vision tests and analyze color discrimination using mathematical models of color spaces. ApproachSix pseudoisochromatic (PIC) tests and two Farnsworth-Munsell (FM) tests were conducted to assess participants’ color vision. Friedman signed rank test was used to compare the outcomes of the Farnsworth-Munsell 100-Hue Tests (FM 100-Hue Tests) between the BBLs and ordinary lenses groups. The CIE color difference formula and a spectral illuminometer were employed to evaluate the color differences with and without BBLs. ResultsAll subjects showed normal outcomes in all PIC tests and Farnsworth-Munsell Dichotomous D-15 Tests (FM D-15 Tests). There were no significant differences between ordinary lenses group and BBLs groups in FM 100-Hue Tests. In the color space, the effect of BBLs on each color light was equivalent to a translation on the CIE 1931 chromaticity diagram with minor distortion. Since BBLs do not disrupt the continuity of the chromaticity diagram, or cause different colors to appear the same, they do not lead to color confusion. However, colors with short wavelengths exhibited more changes in color difference when wearing BBLs. ConclusionsBBLs do not impair the wearer's ability to discriminate colors or perform color vision tests accurately. However, BBLs can cause color differences especially in the recognition of blue hues.

A superpixel‐based color difference detection algorithm for dyed fabrics

AbstractIn order to enhance the accuracy and efficiency of color difference detection for dyed fabrics, this article introduces a novel superpixel‐based color difference detection algorithm, which exhibits three significant improvements over the previous algorithm. First, it proposes a more rational color feature extraction method to extract more detailed color features from fabric images, which uses superpixels as basic units for both color feature extraction and color difference detection. Second, the algorithm employs the CIEDE2000 color difference formula to calculate color difference values. This eliminates the need for obtaining standard fabric images as references in advance, making the process more convenient and practical. Finally, an area‐based color difference calculation method is proposed based on the human visual mechanism, ensuring that the evaluation results are more consistent with human eye observations. Experimental results demonstrate that the proposed algorithm provides more accurate and visually consistent color difference assessments compared to the previous algorithm.

The Effect of Aging on Artificial Saliva at Different pH Values on the Color Stability of New Generation Denture Base Materials.

New-generation denture base materials are used successfully in denture fabrication; however, the effect of saliva pH change on the color stability of materials is unknown. The purpose of this in vitro study is to evaluate the color stability of new-generation denture base materials after immersion in artificial saliva with different pH values (3,7,14). Disc-shaped samples (Ø 10 mm x 2 mm) were prepared from three different denture base materials (1 pre-polymerized polymethylmethacrylate [PMMA], 1 graphene-reinforced PMMA, and heat-cure polymethyl methacrylate resin) (n=10). After polishing, color coordinates were measured using a PCE-CSM 5 colorimeter programmed in the CIE system (L* a* b*). The samples were kept in artificial saliva at different pH values and 37°C for 21 days. At the end of 21 days, color coordinates were measured again. The suitability of the measurements for a normal distribution was examined with the Kolmogro-Smirnov test. Whether color measurements obtained at different pH levels differed according to groups was examined with the Kruskal-Wallis test. The correlation between the CIEDE2000 and CIELab color difference formulas was examined by correlation analysis. The highest color difference occurred in heat-cure samples at pH 3 (p<0.001). The color difference at different pH values was least observed in pre-polymerized PMMA samples. Significant color differences occurred in the graphene-reinforced pre-polymerized PMMA group at pH 7 (p<0.001). It was observed that color differences occurred in all groups. Dentures made of new-generation CAD/CAM PMMA, which are less exposed to color differences, can be recommended for elderly patients with systemic diseases who are frequently exposed to pH changes in the oral cavity. Color differences on denture surfaces over time negatively affect aesthetics. Since pH changes cause changes on the prosthesis surface, it may be recommended for these patients to fabricate dentures from new-generation CAD/CAM PMMA resins, which are less deformable.

Harmonizing color measurements in dentistry using translucent tooth-colored materials

BackgroundSince color measurements are relative, the discrepancy among different instruments is alarmingly high. This multicenter study evaluated the effectiveness of instrument calibration and inter-instrument harmonization of different spectrophotometers with the same optical geometry using tooth-colored, translucent dental materials.MethodsThe coordinating center (CC) spectrophotometer was calibrated using the NPL Ceram Series II set. Two sets of 10 specimens, labeled 1 to 10 and I to X (10 mm in diameter and 1 mm thick), were tested at CC and three research sites (RS1, RS2, and RS3) using the same d/8° optical geometry spectrophotometers. Calibration factors were calculated for each material and site to obtain the average calibration factors for sets 1–10, set I-X, and the combination of both. The differences among the non-corrected and corrected reflection values were calculated using CIEDE2000 (DeltaE00) and CIELAB (DeltaEab) color difference formulas and were submitted to ANOVA and Tukey test (α = 0.05).ResultsA significant decrease of color differences between non-corrected as compared to corrected measurements was recorded for all CC-RS and RS-RS comparisons. The reduction of DeltaE00 values between non-corrected and corrected for CC-RS1, CC-RS2, and CC-RS3 were 83.1%, 77.2%, and 73.6%, respectively. The corresponding DeltaE00 values for RS1-RS2, RS1-RS3, and RS2-RS3 comparisons, indirectly compared in the experiment, were 84.2%, 82.8%, and 68.5%, respectively. There was a significant reduction of DeltaE00 and DeltaEab color difference for all combined RS pairs and each of three RS pairs, corrected with one of two specimen sets calibration factors separately.ConclusionsCalibration and harmonization of color measurements in dentistry using tooth-colored, translucent restorative materials significantly decreased measurement discrepancies between the coordinating center and research sites and among pairs of research sites.

A comparative study on the difference of color space conversion based on table look-up method and neural network

A comparative study on the difference of color space conversion based on table look-up method and neural network

Influence of Composition and Thickness on The Color and Translucency of Glass-Ceramic Materials for Laminate Veneer Restorations: An In Vitro study

Statement of the problem: Numerous glass-ceramic materials are commercially available, yet achieving optimal esthetic results relies significantly on material composition and thickness. The selection of suitable material and thickness poses an ongoing challenge in clinical practice. Objective: This study aimed to investigate the effect of the composition and thickness of different glass-ceramic materials on the Commission Internationale de l'éclairage (CIE) L*, a*, and b* color coordinates and the translucency parameter (TP00). Materials &amp; Methods: Glass-ceramic blocks of A2 shade, with low translucency, encompassing feldspathic (FS), leucite-reinforced feldspathic (LR), and lithium-disilicate (LD) compositions, were sectioned into three thicknesses: 0.5 mm, 0.7 mm, and 1 mm (n=10). All specimens were polished with ceramic polishing rubbers. Using a spectrophotometer, the CIE L*, a*, and b* color coordinates of the specimens were measured over gray, white, and black backgrounds. The TP00 was calculated using the CIEDE2000 color difference formula. The CIE L*, a*, b*, and TP00 were analyzed using two-way ANOVA and Tukey HSD post-hoc tests (α=0.05). Results: Material, thickness, and their interaction significantly influenced the CIE L*, a*, b*, and TP00 values (P&lt;0.001). The LR group displayed the highest L* and a* values, while the LD group showed the lowest (P&lt;0.001). Conversely, the LD group exhibited the highest b* value (P&lt;0.001). Lightness was lowest in 0.5 mm-thick specimens (P&lt;0.001) and similar for 0.7 mm-thick and 1.0 mm-thick specimens (P&gt;0.05). Redness and yellowness increased with increasing thickness (P&lt;0.001). Regardless of thickness, the FS group had the highest TP00 (16.32±1.54), while the LR group had the lowest TP00 (14.31±1.67). Regardless of material, 0.5 mm-thick specimens demonstrated significantly higher TP00 (17.49±1.10) than 0.7 mm-thick (15.45±0.83) and 1.0 mm-thick (13.11±1.12) specimens. There was no significant difference between the 0.5 mm-thick FS and LD groups (P&gt;0.05) and 1.0 mm-thick LR and LD groups (P&gt;0.05). Conclusions: Even when sharing the same shade, glass ceramics may exhibit varying color and translucency properties due to their distinct chemical compositions and thicknesses.

Analysis of Colour Differences Obtained by Acceptability and Perceptibility Threshold (Visual Method):-Review

Backgrounds: Various information about acceptability (AT) and perceptibility thresholds (PT) for colour differences (∆E) was reviewed in dental literatures. There is consensus that determining (∆E) is ideal for identifying AT and PT. However, there is confusion about which values should be used. The aim of this review was to determine the discrepancies in research results and the critical value of ∆E. Materials and methods: MEDLINE/PubMed and Google Scholar were screened for studies that investigated colour acceptability, perceptibility, ∆E, but were not sensitive to whether only AT or PT were used. 20 studies matched the study criteria and had been included in this review and clinical measurements were made using spectrophotometers. Result: Most studies evaluated PT using approximately ∆E = 0.8–1.7. In terms of AT which ranged between 1.8 and 3.7 as a maximum. Many recent studies evaluate AT00=1.8 according to the CIE2000 colour difference formula. Conclusion: Different formulas as ∆E00 (2000) or ∆Eab(lab) in colour expression may produce different results. The CIElAB formula (ΔEab) has greater evidence; however, current research recommends the CIE2000 formula ∆E. The absence of colourimetric control has a negative effect on overall product quality.

A Study on DNN-Based Practical Model for Predicting Spot Color

The color of product packaging plays an important role in brand awareness and consistency. Given the importance of consistent color reproduction, the use of standardized spot colors is essential. However, the reproduction of specific spot colors in offset packaging printing involves additional processes and costs. This study presents an efficient approach to predict the color result of spot color inks in the packaging printing industry, using only the amount of ink involved in the mixing process as an input. Using a neural network-based model, our approach uses the CIEDE2000 color difference formula as a loss function to accurately estimate the final color. This method provides a simplified alternative to traditional color mixing techniques, which often involve subjective judgment and can be resource-intensive. Particularly beneficial for smaller companies, our approach reduces the complexity and cost associated with achieving accurate spot colors. The significance of this work lies in its practical application, providing a simpler, more objective and cost-effective solution for consistent color reproduction in packaging printing.

Evaluation of the Effects of Digital Manufacturing, Preparation Taper, Cement Type, and Aging on the Color Stability of Anterior Provisional Crowns Using Colorimetry.

BACKGROUND Replicating the 3-dimensional (3D) color of natural teeth in artificial substitutes is challenging. Fixed dental prosthodontics require aesthetic, color-stable provisional restorations. Recent milling and 3D printing digital manufacturing techniques offer improved outcomes. This study assesses color stability in various digital manufacturing methods, tapers, and aging effects on anterior provisional resin restorations. MATERIAL AND METHODS Two all-ceramic tooth preparations on typodont teeth with 10° and 20° tapers were converted into experimental dies. Forty temporary crowns were manufactured using 3D printing and computer-aided design/computer-aided manufacturing (milling). Within these 2 groups, 10 crowns were cemented using a regular and clear provisional cement. All samples were thermocycled to simulate clinical use of 6 months. Color difference formula (CIEDE2000) indicated changes between before and after cementation (ΔE00) and between after cementation and after thermocycling (ΔE00[II]). The color change was considered significant in terms of clinically perceptible (ΔE00 ≤0.62) and acceptable (ΔE00 ≤2.62) changes. One-way ANOVA (P value of less than 0.05) calculated overall differences, which were established using a Fisher post hoc test. RESULTS Crowns cemented with clear cement showed fewer color changes irrespective of the manufacturing technique or taper. Notably, only the 10° 3D-printed crown with clear cement had an imperceptible color change at the pre-/post-cementation phase. Meanwhile, the 10° and 20° milled crowns with regular cement exhibited unacceptable color changes after thermocycling. CONCLUSIONS For long‑term temporization in the aesthetic zone, properly optimized 3D-printed provisional restorations cemented with clear cement had better color stability.

Preliminary colour characterisation of a Stratasys J750 digital anatomy printer with different fillings and face orientations

Multicolour capability in additive manufacturing could play a key role in certain applications such as surgical training and consumer products. However, the ability to accurately 3D print colours is not well documented and could affect the realism of models produced through these technologies. As a recent system, the Stratasys J750 Digital Anatomy Printer has yet to be analyzed for its colour perception and accuracy, which is quantified through this study. This will allow users of this and similar material jetting systems with an improved understanding of the relationship between digitally applied colours and their result when 3D printed, as well as the influence of certain settings. Thirty-three rectangular prism models with different CMYK and RGB colours, as well as infill materials, were printed on a Stratasys J750 DAP printer. These were scanned on five faces using a Nix Mini 2 handheld colour sensor, documenting readings in CIELAB format. The data were analyzed using the CIEDE2000 colour difference formula, and its recent modifications for 3D printed objects. Results found statistically significant and perceptive differences in colour accuracy among different colours, core materials, and face orientations. It was also observed that the addition of VeroPureWhite as filler material instead of the default SUP706 support improved colour accuracy. The study recommends the following steps to improve colour accuracy: (i) avoid the addition of black (K) manually in CMYK colour space, (ii) use pure white as the base infill material instead of support material, (iii) add a little white (~ 10%–30%) to make samples opaque instead of translucent.

Research on fabric image registration and color difference detection based on cyclic elements

In order to realize online color difference detection of printed fabrics, a color difference detection method of printed fabrics based on image segmentation and image registration was proposed to detect the color difference of simple printed fabrics. The acquired standard fabric images are segmented using the combination of a Canny edge detector and uniform grid partitioning. The color information of each sub image is extracted based on the segmentation results and saved. We use the speeded-up robust features algorithm that incorporates the position information of the cyclic element where the feature points are located. The segmentation path of the standard image is registered onto the fabric image to be detected. The color information of each sub image of the image to be detected is extracted according to the registered segmentation path. The color difference value between the sub image of the image to be detected and the sub image of the standard sample is calculated using the CIEDE2000 color difference formula. The experimental results show that when fabric images with duplicate patterns are registered, the image registration methods mentioned in this paper significantly improve the accuracy of registration. The accuracy of the detection method in this paper on the printed fabric dataset can reach 95% compared to the manual calibration results.

A machine learning approach to color space Euclidization

AbstractIn this work, a machine learning methodology is proposed for the issue of color space Euclidization. Given a color difference formula as reference distance law, the Euclidization task consists in finding an injective transformation from the original color space into a real vector space and the corresponding inverse transformation, such that the Euclidean distances in the embedded color space align with the reference color distances. For this, artificial neural networks are devised as function approximators for the color space transformations being sought. Training these neural networks is accomplished through unsupervised learning, making use of random sampling and gradient descent. As key disagreement measure, either the (symmetric) relative isometric disagreement or the standardized residual sum of squares (STRESS) index is considered at a time and incorporated as part of the optimization criterion into the objective function. Comparative evaluation is carried out on well‐established color distance laws, including the CIELAB‐based DE2000 color difference formula. The evaluation results indicate significant performance advantages of the proposed approach over previous contributions.

An investigation of color difference for binocular rivalry and a preliminary rivalry metric, ΔE*bino

AbstractHead‐mounted displays (HMDs) for virtual and augmented reality applications could have severe nonuniformities due to complex optical components and the choice of light source technologies. In addition, module variations between the two eyes can result in different colors being seen with the left and right eyes. Binocular rivalry is expected for large color differences between the two eyes, which can severely affect product usability. Thus, it is important to characterize and predict the binocular rivalry in HMDs caused by interocular color differences. As a step toward this end, we propose the first binocular color difference metric, ΔE*bino, to predict the just noticeable binocular rivalry for a pair of solid colors. A psychophysical experiment was conducted using Meta Quest 2, in which we presented different colors to the left and right eye. The collected data were analyzed to derive the metric using ROC curves. We show that the ΔE*bino metric showed significant improvements over conventional color difference formulae. Both the ΔE*bino formula and the anonymized experiment results are available for download.

Visual color inspection with a hyperspectral camera: inline application for automotive parts production

The development of cars is becoming increasingly focused on colour, which is a major challenge for both suppliers and manufacturers. Manufacturers must establish strict colour tolerances for each coloured component and specify both colour and appearance. On the other hand, suppliers must maintain colour accuracy in part production, regardless of the type of material used, to ensure acceptance of colour by automotive manufacturers. In the colour industry, colour difference formulas are used to make unbiased judgments about whether manufactured goods should be approved or disapproved. These objective judgments are based on instrumental colour measurements that must accurately predict subjective colour variations. Hyperspectral imaging (HSI) has proven to provide helpful data for a variety of applications in numerous industries, including colour science. To measure and analyse colour differences between automotive parts, we proposed to use conventional colour science algorithms in conjunction with the Specim FX10 hyperspectral camera, which has a flexible infrastructure that can receive data from a Generic Interface for Cameras (GenICam) compatible with the Gigabyte Ethernet interface. The results showed that the use of hyperspectral imaging in production offers great potential for providing real-time colour information so that colour shifts can be detected early and costly errors in the production line can be avoided.

Dyeing of polyamide fabrics with a reverse micellar system using soybean oil as a solvent

AbstractThe current study reports the results of non‐aqueous dyeing on polyamide fabrics based on a reverse micellar system composed of a stable emulsion of soybean oil, a co‐surfactant, a nonionic surfactant and acid dyes. The system does not make use of water or electrolytes and significantly reduces the dyebath volume. The influence of the hydrophilic lipophilic balance of the surfactants was evaluated, and it was found that the more hydrophilic the surfactant, the better the interaction of the reverse micellar emulsion with the substrate and, consequently, the greater the resulting colour strength. The co‐surfactant plays an important role in the system, as its proportion to the surfactant/oil mixture is directly related to better exhaustion of the dyebath. The results were compared with those from a conventional water‐based dyeing system. Colour matching was performed using the CIELab colour difference formula (ΔE) measured by a reflectance spectrophotometer.