A general geometrical model for predicting color mixing of woven fabrics from colored warp and filling yarns

Seyam, Abdel‐Fattah M.; Mathur, Kavita

doi:10.1007/s12221-012-0795-3

Cited by 19 publications

(26 citation statements)

References 23 publications

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“…In addition, because K and S of the opaque fibers are additive, the relationship between the K/S value of the color blending fabric and the ratio of each monochromatic fiber is denoted as Equation according to the K‐M theory:

\frac{K}{S} = \frac{\sum_{i = 1}^{n} C_{i} K_{i}}{\sum_{i = 1}^{n} C_{i} S_{i}}

where i = 1, ..., n is the monochromatic blending ratio, C i ( i = 1, …, n ) is the blending ratio of each component in the blending yarn, K i , S i are K and S values of each type of fibers in the yarn.…”

Section: K‐m Double Constant Theorymentioning

confidence: 99%

“…The least squares method was proposed by Walowit using the linear least squares regression algorithm to solve the K and S values, so that the color difference between the calculated and the measured is minimal . Some researchers, using the least squares method to study blended colors with the three primary colored fibers (red, yellow, and blue), have been satisfied with the results . The relative value method was proposed by Burlone in the study of blending effects of nine colored nylon fiber.…”

Section: Introductionmentioning

confidence: 99%

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K‐M theory of fabric knitted by three‐channel rotor spun wool yarn

Yang

Deng

et al. 2018

Color Research & Application

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Two‐component and three‐component color blended yarns were spun by red, yellow, and blue wool slivers using a three‐channel rotor spun machine, and the corresponding plain fabrics were knitted. The color‐matching models of K‐M theory were built with the relative method and the least squares method, respectively. Colors and blending ratios of the fabrics were predicted by the model. The results showed that the average color differences of the samples predicted by the two methods are both about 1.0 and the mean value of the proportional error is below 3%. The least squares method has a better color‐matching effect for the three‐component sample, and the relative value method has better color‐matching results for the two‐component sample. When the tolerance range is 2.0, the pass rates of the samples predicted by either the relative value method or the least squares method reach 100%.

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\frac{K}{S} = \frac{\sum_{i = 1}^{n} C_{i} K_{i}}{\sum_{i = 1}^{n} C_{i} S_{i}}

Section: K‐m Double Constant Theorymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

K‐M theory of fabric knitted by three‐channel rotor spun wool yarn

Yang

Deng

et al. 2018

Color Research & Application

View full text Add to dashboard Cite

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“…Stearns and Noechel further extended the application of their formula to other wavelengths, which led to the development of the final form of their formula : (6) here, the empirical parameter M is a variable, which was found to be 0.15 for fine wool through experiments. Function f requires M to be determined experimentally.…”

Section: Stearns-noechel Modelmentioning

confidence: 99%

“…Compared with the actual coverage of yarns, certain errors inevitably occur when a theoretical geometric model is used to calculate the area coverage of each yarn component on a fabric surface. According to preliminary research on the color prediction of woven fabric, when the CIELAB color space is used, values of 2 < ΔE * ab < 5 are considered satisfactory, and values of ΔE * ab > 5 mean that improvement is required [5][6][7].…”

Section: Color Differencesmentioning

confidence: 99%

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Optimized Stearns-Noechel Model to Predict Mixed Color Values of Yarn-Dyed Fabrics

Zhang

Jin

et al. 2014

Sen-i Gakkaishi

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Three‐dimensional color prediction modeling of single‐ and double‐layered woven fabrics

Chae

Hua

Xin

2017

Color Research & Application

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In this research, the three-dimensional structural and colorimetric modeling of threedimensional woven fabrics was conducted for accurate color predictions. Onehundred forty single-and double-layered woven samples in a wide range of colors were produced. With the consideration of their three-dimensional structural parameters, three-dimensional color prediction models, K/S-, R-, and L*a*b*-based models, were developed through the optimization of previous two-dimensional models which have been reported to be the three most accurate models for single-layered woven structures. The accuracy of the new three-dimensional models was evaluated by calculating the color differences DL*, DC*, Dh8, and DE CMC(2:1) between the measured and the predicted colors of the samples, and then the error values were compared to those of the two-dimensional models. As a result, there has been an overall improvement in color predictions of all models with a decrease in DE CMC(2:1) from 10.30 to 5.25 units on average after the three-dimensional modeling. K E Y W O R D Scolor prediction, color prediction model, double-layered fabric, single-layered fabric, three-dimensional modeling | I NT ROD UCTI ONThe colors of woven fabrics depend on the weave structures as well as the individual yarn colors used. In the current practice of designing woven fabrics, targeted colors are achieved using computer-aided design (CAD) systems in which designers allocate weaves and yarn colors appropriately to the original designs displayed on computer screens. By checking the visual simulations of final fabrics provided by the CAD systems, designers can easily recolor their designs as required. In this process, accurate visual simulations based on accurate color prediction models predicting combined weave-color effects will reduce or even eliminate the need for physical sampling, a time-consuming and costly process, before actual production. Nevertheless, there has not been sufficient research 1-10 on the color prediction modeling of woven fabrics. The color prediction modeling of woven fabrics has been conducted in three steps: (1) geometric modeling of woven structures to calculate the proportion of each yarn color on the fabric surface, (2) colorimetric modeling to calculate the final color attributes, L*, a*, b*, C*, and h8 values, of the fabrics from the calculated proportions and the color attributes of yarns using some color prediction models (also known as color mixing models), and (3) accuracy evaluation of the color predictions by calculating the difference between the measured and the predicted color attributes of the fabrics. [1][2][3][4][5][6][7][8][9][10] In the previous research, the geometric modeling was conducted with the use of single-layered woven fabrics based on the assumption that fabrics have two-dimensional flat structures. This two-dimensional modeling simplifies the modeling of complex three-dimensional woven structures, and the resultant geometric model can be used easily in industry. In the next step, colorimetric modeling,...

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A general geometrical model for predicting color mixing of woven fabrics from colored warp and filling yarns

Cited by 19 publications

References 23 publications

K‐M theory of fabric knitted by three‐channel rotor spun wool yarn

K‐M theory of fabric knitted by three‐channel rotor spun wool yarn

Optimized Stearns-Noechel Model to Predict Mixed Color Values of Yarn-Dyed Fabrics

Three‐dimensional color prediction modeling of single‐ and double‐layered woven fabrics

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