Use of a predictive colour model for managing the colour appearance of two‐colour woven fabrics

The aim of this study was to implement a two‐dimensional colour appearance model for prediction of the colour values of weft threads when the optical mixing of a two‐colour woven structure had to match the colour appearance of a single‐colour reference woven fabric. Five single‐colour woven fabrics were woven from five threads of similar hue. One of the samples was chosen as a reference, for which the colour appearance was the goal to be achieved in the two‐colour woven fabrics prepared with the other available warp threads and newly dyed weft threads. The colour values of dyed weft threads were predicted by a two‐dimensional colour appearance model. With dyed weft threads, managing the colour appearance of the two‐colour woven fabric was enabled to achieve the colour values of the reference. In the results, colour deviations between the predicted and measured colour values of weft threads revealed some limitations to the colour appearance model and performance of the dyeing process. After the production of the two‐colour woven fabric, the colour appearance matched the appearance of the reference, resulting in deviations of ΔE_CMC(2:1) = 1.2‐7.8. Moreover, the differences between theoretically predicted and measured colour values of the two‐colour woven fabric were evaluated as small, ranging from ΔE_CMC(2:1) = 1.5‐1.9. The results demonstrated the efficiency of implementing the colour appearance model and the dyeing process of weft threads as an approach to achieve the defined colour appearance of two‐colour woven fabrics, which with small colour deviations matches the colour of a single‐colour reference.     

Use of regression methods for determining the relation between theoretical–linear and spectrophotometrical colour values of bicolour woven structures

In this paper, new approaches for evaluating the entire colour effect of optical mixing of bicolour woven structures are presented. Simple woven structures with constant colour in the warp direction and different colours in the weft direction were prepared and analysed. The constructional parameters of these woven fabrics were systematically changed, which resulted in the variations of the fractions of colour components and, consequently, also in the changes of colour properties (lightness, hue, chroma) of bicolour optical mixtures. The position of colours of the bicolour structures and the approximate direction (linear) of colour changes in CIELAB colour space were theoretically determined with a simple geometrical model and additive method. Furthermore, the bicolour optical effects were determined spectrophotometrically. The differences between the linear–theoretical and the spectrophotometrical colour values of bicolour woven fabrics were mathematically analysed with linear and non‐linear regression methods to determine the positions of colour coordinates L*, a* and b* of bicolour woven fabrics in the a*b* plane by increasing or reducing the cover factors of warp and weft threads (addition or reduction of colour components). The results present, on the one hand, the strong influence of original colours of warp and weft threads and, on the other hand, the minor influence of constructional parameters on the form of linear/non‐linear behaviour of colours of bicolour compositions. When the characteristics of a specific colour combination are taken into account, the spectrophotometrical colour values of bicolour woven fabrics can be also mathematically determined with additive–theoretical colour values and, to some extent, with predictable colour deviations.     

Colour change as a result of textile transformations

This paper studies the influence of textile structure on its colour. It provides a systematic analysis of the changes in spectral reflectance and hence colour differences between three textile substrates: roving, yarn and woven fabric. The transformations of the reflectance spectrum as a result of the changes of the structure were modelled and the evolutions of the colorimetric coordinates L *, a *, b *, C * and h associated with these various transformations were thus calculated and analysed. The work also offers a useful method of modelling the predicted colour from one substrate form to another, which is important to the textile industry.     

Towards automation of color/weave selection in Jacquard design: Model verification

Jacquard woven fabrics are made from colored yarns and different weaves for designing complex pictorial and other patterning effects. The final visualized color effect is the result of assigning weave designs to different areas of the pattern to be created. The current practice in creating Jacquard woven fabric designs is to produce many samples in a trial‐and‐error attempt to match artwork colors. An ability to simulate accurately the appearance of a design prior to manufacture is highly desirable to reduce trial‐and‐error sample production. No automated accurate digital color methodology is yet available to assist designers in matching the patterned woven fabric to the desired artwork. To achieve this, we developed a geometrical model to predict the color contribution of each yarn on the face of the fabric. The geometrical model combined with a Kubelka‐Munk based color mixing model allowed the prediction of the reflectance properties of the final color for a given design. We compared the predicted and experimental values of the reflectance properties for a range of fabrics using the same geometric model with three separate color mixing models. The geometrical model combined with a log‐based color mixing model produced reasonable agreement between predicted and measured ΔE_ab, with an average ΔE_ab of approximately five. © 2009 Wiley Periodicals, Inc. Col Res Appl, 34, 225–232, 2009     

A colour harmony model for two‐colour combinations

This study investigates harmony in two‐colour combinations in order to develop a quantitative model. A total of 1431 colour pairs were used as stimuli in a psychophysical experiment for the visual assessment of harmony. These colour pairs were generated using 54 colours selected systematically from CIELAB colour space. During the experiment, observers were presented with colour pairs displayed individually against a medium gray background on a cathode ray tube monitor in a darkened room. Colour harmony was assessed for each colour pair using a 10‐category scale ranging from “extremely harmonious” to “extremely disharmonious.” The experimental results showed a general pattern of two‐colour harmony, from which a quantitative model was developed and principles for creating harmony were derived. This model was tested using an independent psychophysical data set and the results showed satisfactory performance for model prediction. The study also discusses critical issues including the definition of colour harmony, the relationship between harmony and pleasantness, and the relationship between harmony and order in colour. © 2006 Wiley Periodicals, Inc. Col Res Appl, 31, 191–204, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20208     

Spectral dependence of colorimetric characterisation of scanners

The spectral dependence of the colorimetric characterisation of a typical scanner was investigated. Different colour sets, including ColorChecker SG, Kodak Q‐60 colour input target, a set of plain woven coloured fabrics with a large colour gamut, and randomly selected samples of the Munsell Book of Color were used as training and testing sets in the colorimetric characterisation of a scanner by employing a non‐linear regression method. The coefficient matrices were optimised for each particular media in the training stage and used to predict the device‐independent colorimetric data, i.e. CIELab values of other media from their corresponding RGB values measured by the scanner. In order to extract the differences between the applied sets and determine the actual dimensions of their reflectance spectra, the principal component analysis technique was employed. As expected, it was observed that the different sets benefit from diverse dimensional properties and, in some cases, the spectral behaviours of the first few eigenvectors were apparently different. It was demonstrated that scanner colorimetric characterisation depended on the spectral properties of the applied colour set in the training stage and, consequently, the testing errors increased with increasing the spectral dissimilarity between the sets that were used in training and testing sequences. It was concluded that, to achieve better colour reproduction results, the scanner should be characterised for each media with specific spectral properties.     

Gamut evaluation of an n‐colour printing process with the minimum number of measurements

The aim of this study was to use a minimum number of measured colour patches to evaluate the colour gamut of an n‐colour printing process. Traditionally, the colour gamut of a printing system has been derived by printing and then measuring a gamut target for example, a profiling chart. For an n‐colour printing (printing with more than four process inks), it is desirable to know the colour gamut of the given set of inks without having to print a large number of test patches. Different spectral printer models were used to predict the gamut of a 7‐colour printing process. The colorant space was divided into sectors each containing four inks. For each printer model, the colour gamut of the each four‐ink sector was predicted. All sector‐gamuts were then combined to predict the overall colour gamut of the n‐colour process. This predicted gamut was then compared with the gamut obtained by measurement using a gamut comparison index (GCI). The Yule–Nielsen modified spectral Neugebauer (YNSN) model gave the best accuracy, at the cost of a larger number of input measurements, than other models. A combination of the Kubelka–Munk (KM) and YNSN models performed well with the fewest input measurements. © 2014 Wiley Periodicals, Inc. Col Res Appl, 40, 408–415, 2015     

An intelligent system for fashion colour prediction based on fuzzy C‐means and gray theory

For design and manufacturing industries, to be able to capture the fashion trend is an essential factor that leads to winning a sale. However, colour predicting process in many organizations is not visible to the public. In order to provide colour trend to industries in advance, a predicting method is proposed in this study. In the method, the fuzzy c‐means was used to separate the collected colour data, then the minimum mean‐square error was used to place the similar colour clusters within different time point together and the gray model was adopted for prediction. In order to verify the prognostication of the system, four data announced by Pantone from spring 2014 to fall, 2015 were taken as the predicted samples and the colour for spring 2016 was predicted to compare with that in Pantone spring, 2016. The results show that the system has a high accuracy for predicting colour. The residual modified model constructed with the colour samples rearranged with MMSE has the best‐predicted result that ranged from 83.3% to 99.4%. It indicates that the result obtained with the rearranged samples is higher than that without rearrangement. Besides, the accuracy of the gray predicted results with residual modification would be more precise than the one without residual modification. Moreover, the value of mean squared error is quite low, which was ranged from 0.000025 to 0.0277. Therefore, the current intelligent predicting system satisfies the criteria of capturing colour in trend for enterprises. Moreover, it enables industries to make decisions for selecting the colour trend. © 2016 Wiley Periodicals, Inc. Col Res Appl, 42, 273–285, 2017     

A novel approach to using neural networks to predict the colour of fibre blends

This work is concerned with the colour prediction of viscose fibre blends, comparing two conventional prediction models (the Stearns–Noechel model and the Friele model) and two neural network models. A total of 333 blended samples were prepared from eight primary colours, including two‐, three‐, and four‐colour mixtures. The performance of the prediction models was evaluated using 60 of the 333 blended samples. The other 273 samples were used to train the neural networks. It was found that the performance of both neural networks exceeded the performance of both conventional prediction models. When the neural networks were trained using the 273 training samples, the average CIELAB colour differences (between measured and predicted colour of blends) for the 60 samples in the test set were close to 1.0 for the neural network models. When the number of training samples was reduced to only 100, the performance of the neural networks degraded, but they still gave lower colour differences between measured and predicted colour than the conventional models. The first neural network was a conventional network similar to that which has been used by several other researchers; the second neural network was a novel application of a standard neural network where, rather than using a single network, a set of small neural networks was used, each of which predicted reflectance at a single wavelength. The single‐wavelength neural network was shown to be more robust than the conventional neural network when the number of training examples was small.     

Temperature‐dependent tensile strength model for 2D woven fiber reinforced ceramic matrix composites

This paper presents a temperature‐dependent model for predicting the tensile strength of 2D woven fiber reinforced ceramic matrix composites. The model takes into account the combined effects of temperature, temperature‐dependent residual thermal stress, temperature‐dependent matrix strength, and fibers strength on the tensile strength of composites. To verify the model, the tensile strengths of 2D woven fiber reinforced ceramic matrix composites available are predicted at different temperatures. The model predictions agree well with the experimental data. This work could provide a practical technical means for predicting the temperature‐dependent tensile strength of 2D woven fiber reinforced ceramic matrix composites and uncovering the dominated mechanisms leading to the change of tensile strength and their evolution with temperature.     

Psychophysical models of consumer expectations and colour harmony in the context of juice packaging

The aim of this study was to develop psychophysical models that predict the influence of pack colours on consumers' psychological responses of fruit juices, such as visually perceived expectations of freshness, quality, liking, and colour harmony. Two existing colour harmony models derived from experiments involving only uniform colour plaques were tested using the juice packaging experimental data. Both models failed to predict the visual results obtained. Nevertheless, two parameters relevant to chromatic difference and hue difference were somewhat associated with the visual results. This suggested that, among all colour harmony principles for uniform colours, only the equal‐hue and the equal‐chroma principles can be adopted to describe colour harmony of packaging used for juice. This has the implication that the principles of colour harmony may vary according to the context in which the colours are used. A new colour harmony model was developed for juice packaging, and a predictive model of freshness was derived. Both models adopted CIELAB colour attributes of the package colour and the fruit image colour to predict viewers' responses. Expected liking and juice quality can be predicted using the colour harmony model while expected freshness can be predicted using the predictive model of freshness. © 2013 Wiley Periodicals, Inc. Col Res Appl, 40, 157–168, 2015     

Investigation of texture effect on visual colour difference evaluation

The texture effect on visual colour difference evaluation was investigated in this study. Five colour centers were selected and textured colour pairs were generated using scanned textile woven fabrics and colour‐mapping technique. The textured and solid colour pairs were then displayed on a characterized cathode ray tube (CRT) monitor for colour difference evaluation. The colour difference values for the pairs with texture patterns are equal to 5.0 CIELAB units in lightness direction. The texture level was represented by the half‐width of histogram, which is called texture strength in this study. High correlation was found between texture strength and visual colour difference for textured colour pairs, which indicates that an increasing of 10 units of texture strength in luminance would cause a decreasing of 0.25 units visual difference for the five colour centers. The ratio of visual difference between textured and solid colour pairs also indicates a high parametric effect of texture. © 2005 Wiley Periodicals, Inc. Col Res Appl, 30, 341–347, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.     

Additivity of colour harmony

An additive approach to predict harmony for three‐colour combinations is proposed in this article. It is hypothesised that a three‐colour combination can be seen as a combination of three colour pairs, each generating a harmonious/disharmonious feeling that can be quantified by a two‐colour harmony model the authors previously derived; the average of these three harmony values can then determine the overall harmony. To establish whether this hypothesis was valid, two psychophysical experiments were conducted in the United Kingdom and the United States. Experiment 1 used 6545 three‐colour wheels as the stimuli, presented individually on a calibrated cathode ray tube display. Under the same viewing conditions, Experiment 2 used 111 interior images as the stimuli. In each experiment, 20 British and 31 American participated as the observers. An additional test was undertaken, with 64 observers taking part, to address the issue of large sample size as encountered in Experiment 1, using 90 colour wheels selected randomly from those used in Experiment 1. The experimental results show close agreement between the observers' response and the harmony value predicted by the proposed method, with a correlation coefficient of 0.71 for the 6545 colour wheels, 0.93 for the 111 interior images and 0.88 for the additional 90 colour wheels. The results support the additive approach as a simple but robust method for predicting harmony in any three‐colour combinations, which may also apply to combinations generated by any number of colours. © 2010 Wiley Periodicals, Inc. Col Res Appl, 2011     

A comparison of colour appearance for surface colours between outdoor and indoor environments

Psychophysical experiments of colour appearance, in terms of lightness, colourfulness, and hue, were conducted outdoors and indoors to investigate whether there was any difference in colour appearance between outdoor and indoor environments. A panel of 10 observers participated in the outdoor experiment, while 13 observers took part in the indoor experiment. The reference white had an average luminance of 12784 cd/m² in the outdoor experiment and 129 cd/m² in the indoor experiment. Test colours included 42 colour patches selected from the Practical Coordinate Color System to achieve a reasonable uniform distribution of samples in CIECAM02. Experimental results show that for both outdoor and indoor environments, there was good agreement between visual data and predicted values by CIECAM02 for the three colour appearance scales, with the coefficient of variation values all lower than 25 and the R² values all higher than 0.73, indicating little difference in the three dimensions of colour appearance between indoor and outdoor viewing conditions. Experimental data also suggest that the observers were more sensitive to variation in lightness for grayish colours than for highly saturated colours, a phenomenon that seems to relate with the Helmholtz-Kohlrausch effect. This phenomenon was modeled for predicting perceived lightness (J′) using the present experimental data. The new J′ model was tested using three extra sets of visual data obtained both outdoors and indoors, showing good predictive performance of the new model, with an average coefficient of variation of 14, an average R² of 0.88, and an average STRESS index of 14.18.     

A cross‐cultural colour‐naming study. Part I: Using an unconstrained method

Colour naming by panels of British and Taiwanese subjects (speaking English and Mandarin, respectively) was used to study colour categorization, and the results applied to investigate differences of usage between the two languages. Fifty British and 40 Chinese subjects took part in experiments using an unconstrained method with 200 ISCC‐NBS colour samples. Data analysis was performed to calculate the frequency and codability of each colour name in each group and subgroup. These names were then grouped using 7‐category and 4‐category methods to find the culture and gender differences. It was confirmed that the 11 basic names found by Berlin and Kay were the most widely used for both languages. The results showed a close agreement between the two languages in terms of colour categories, but a large discrepancy in the use of secondary names due to cultural differences. The cross‐cultural comparison revealed a clear pattern of the linkage between language and concepts of colour. © 2001 John Wiley & Sons, Inc. Col Res Appl, 26, 40–60, 2001     

Geometric parameters characterization of minicomposite and modulus prediction of 2D composite based on X-ray computed tomography

The reconstruction quality of a three-dimensional (3D) model of woven composites and the mechanical performance of minicomposites have an important influence on the accuracy of finite element (FE) analysis. Through edge detection and morphological operations, the cross-sectional area of a SiC/SiC minicomposite and the volume content of each component were calculated. This method can also be used to obtain the pore distribution. For the SiC/SiC two-dimensional (2D) woven composite, the structure tensor was used to initially classify the weft and warp in the top view of the X-ray computed tomography (XCT) image, and then, the front view was derived to readily correct the misclassification regions. The edge equivalent is proposed because watershed segmentation cannot compute the edge at the overlapping regions. Then, multiple morphological operations were applied to achieve accurate individual warp recognition. Finally, comparing the modulus predicted by the reconstructed FE model with the experimental results, the prediction was found to be in good agreement with the experiment.     

A study of colour emotion and colour preference. Part III: Colour preference modeling

In this study three colour preference models for single colours were developed. The first model was developed on the basis of the colour emotions, clean–dirty, tense–relaxed, and heavy–light. In this model colour preference was found affected most by the emotional feeling “clean.” The second model was developed on the basis of the three colour‐emotion factors identified in Part I, colour activity, colour weight, and colour heat. By combining this model with the colour‐science‐based formulae of these three factors, which have been developed in Part I, one can predict colour preference of a test colour from its colour‐appearance attributes. The third colour preference model was directly developed from colour‐appearance attributes. In this model colour preference is determined by the colour difference between a test colour and the reference colour (L*, a*, b*) = (50, ?8, 30). The above approaches to modeling single‐colour preference were also adopted in modeling colour preference for colour combinations. The results show that it was difficult to predict colour‐combination preference by colour emotions only. This study also clarifies the relationship between colour preference and colour harmony. The results show that although colour preference is strongly correlated with colour harmony, there are still colours of which the two scales disagree with each other. © 2004 Wiley Periodicals, Inc. Col Res Appl, 29, 381–389, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20047     

A cross‐cultural colour‐naming study. Part III—A colour‐naming model

A colour‐naming model was developed to categorize volumes for each of the 11 basic names in CIELAB colour space. This was tested with three different sets of data for two languages (English and Mandarin), derived from extensive colour categorization experiments. The performance of the model in predicting colour names was satisfactory, with an average prediction error of 8.3%. © 2001 John Wiley & Sons, Inc. Col Res Appl, 26, 270–277, 2001     

Mathematical approach for predicting non‐negative tristimulus values using the CAT02 chromatic adaptation transform

It has been reported that for certain colour samples, the chromatic adaptation transform CAT02 imbedded in the CIECAM02 colour appearance model predicts corresponding colours with negative tristimulus values (TSVs), which can cause problems in certain applications. To overcome this problem, a mathematical approach is proposed for modifying CAT02. This approach combines a non‐negativity constraint for the TSVs of corresponding colours with the minimization of the colour differences between those values for the corresponding colours obtained by visual observations and the TSVs of the corresponding colours predicted by the model, which is a constrained non‐linear optimization problem. By solving the non‐linear optimization problem, a new matrix is found. The performance of the CAT02 transform with various matrices including the original CAT02 matrix, and the new matrix are tested using visual datasets and the optimum colours. Test results show that the CAT02 with the new matrix predicted corresponding colours without negative TSVs for all optimum colours and the colour matching functions of the two CIE standard observers under the test illuminants considered. However, the accuracy with the new matrix for predicting the visual data is approximately 1 CIELAB colour difference unit worse compared with the original CAT02. This indicates that accuracy has to be sacrificed to achieve the non‐negativity constraint for the TSVs of the corresponding colours. © 2011 Wiley Periodicals, Inc. Col Res Appl, 2011     

Unique hue data for colour appearance models. Part III: Comparison with NCS unique hues

In this study, Swedish Natural Color System (NCS) unique hue data were used to evaluate the performance of unique hue predictions by the CIECAM02 colour appearance model. The colour appearance of 108 NCS unique hue stimuli was predicted using CIECAM02, and their distributions were represented in a CIECAM02 a_c–b_c chromatic diagram. The best‐fitting line for each of the four unique hues was found using orthogonal distance regression in the a_c–b_c chromatic diagram. Comparison of these predicted unique hue lines (based on the NCS data) with the default unique hue loci in CIECAM02 showed that there were significant differences in both unique yellow (UY) and unique blue (UB). The same tendency was found for hue uniformity: hue uniformity is worse for UY and UB stimuli in comparison with unique red (UR) and unique green (UG). A comparison between NCS unique hue stimuli and another set of unique hue stimuli (obtained on a calibrated cathode ray tube) was conducted in CIECAM02 to investigate possible media differences that might affect unique hue predictions. Data for UY and UB are in very good agreement; largest deviations were found for UR. © 2014 Wiley Periodicals, Inc. Col Res Appl, 40, 256–263, 2015