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

Li, Qizheng; Zhang, Feiyan; Jin, Xiaoke; Zhang, Shengcheng; Zhu, Chunhua

doi:10.2115/fiber.70.218

Cited by 9 publications

(13 citation statements)

References 11 publications

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“…The literature points out that the Stearns‐Noechel model parameters M of the cotton fiber and the wool are related to the wavelength. In this article, the objective is to investigate such relationship for digital rotor spun yarns.…”

Section: Depends On Wavelength (M2)mentioning

confidence: 99%

“…The art of color matching blends of pre‐colored fibers has existed for years. Several methods have been introduced to describe the color blending of pre‐colored fibers, such as Kubelka‐Munk theory, Friele equation, and Stearns‐Noechel model . Among which, Stearns and Noechel proposed the S‐N model for blending black and white wools with a constant parameter M = 0.15.…”

Section: Introductionmentioning

confidence: 99%

“…Philips et al extended the application of the model to cotton fibers of 14 colors with two colors blended together, studying from different angles and obtained a constant M = 0.109 and a non‐definite M varying with wavelength as

M = 0.12 normalλ + 42.75

. Shen et al applied the models to wools colored by five primary colors (black, white, yellow, red and blue), and obtained

M = 0.141 normalλ + 94.266

.…”

Section: Introductionmentioning

confidence: 99%

“…Several methods have been introduced to describe the color blending of pre-colored fibers, such as Kubelka-Munk theory, [4][5][6] Friele equation, [7][8][9] and Stearns-Noechel model. [10][11][12] Among which, Stearns and Noechel 10 proposed the S-N model for blending black and white wools with a constant parameter M 5 0.15. Philips et al 11 extended the application of the model to cotton fibers of 14 colors with two colors blended together, studying from different angles and obtained a constant M 5 0.109 and a non-definite M varying with wavelength as M 5 0:12k 1 42:75.…”

Section: Introductionmentioning

confidence: 99%

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Color matching of fiber blends: Stearns‐Noechel model of digital rotor spun yarn

Yang

Han

et al. 2017

Color Research & Application

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Stearns‐Noechel model was utilized as a primary reference to study color matching principles of digital rotor spun yarn. Three primary colored (red, yellow and blue) cotton fibers were used to spin blended yarns. Spectral reflectance of the two‐component and three‐component samples was measured with data color spectrophotometer. For these samples, the Stearns‐Noechel model parameter M was determined. Four methods were employed to calculate the M value to improve accuracy of the model, 1.Classical method, named as M1; 2.Optimizing the M1 value obtained by the classical method considering the wavelength factor, named as M2; 3.Simplified M2 according to the linear correlation with the wavelength, named as M3; 4. Simplified M2 according to the segmentation correlation with the wavelength, named as M4. The study shows that average color difference of the two‐component decreases from 2.7 to 1.48, and for three‐component samples from 3.32 to 1.66, by using M2 instead of M1. While calculated using M3, the color difference of the two types of samples will be 1.73 and 2.19, correspondingly. This cannot meet color matching needs. As for M4, the average color difference of the two categories will be 1.54 and 1.91, better than the result obtained using M1 and M3, worse than M2.

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Section: Depends On Wavelength (M2)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

M = 0.12 normalλ + 42.75

. Shen et al applied the models to wools colored by five primary colors (black, white, yellow, red and blue), and obtained

M = 0.141 normalλ + 94.266

.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Color matching of fiber blends: Stearns‐Noechel model of digital rotor spun yarn

Yang

Han

et al. 2017

Color Research & Application

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show abstract

“…Color matching blends of precolored fibers have been researched for decades. Several methods have been introduced to describe the color blending of precolored fibers, such as Kubelka‐Munk theory, Friele equation and Stearns‐Noechel model . In recent years, many people have used K‐M to study blending effects with different fiber materials and have achieved satisfactory results.…”

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

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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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Color spectra algorithm of hyperspectral wood dyeing using particle swarm optimization

Guan

et al. 2020

Wood Sci Technol

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To improve the accuracy and practicality of the intelligent color-matching application of wood dyeing technology, Fraxinus mandshurica veneer was selected as the dyeing material. First, based on the Friele model and Stearns–Noechel model, the model parameters were cyclically assigned to calculate the optimal fixed parameter values and predictions. Then, particle swarm algorithm was used to optimize two algorithm models, the obtained reflectance curve was fit, and the color differences were calculated according to the human eye-based CIEDE2000 color difference evaluation standard formula. Last, the two formulas to predict the color difference and spectral reflectance were compared. First, the two optimization algorithms were compared according to the size of the fitted color difference value, and then, the most accurate optimization algorithm was selected. When the model parameters were fixed, the average fitted color difference was 0.8202. After optimizing the Friele model, the average fitted color difference was 0.7287, and after optimizing the Stearns–Noechel model, the average fitted color difference was 0.6482. It was concluded that the improved Stearns–Noechel model based on particle swarm method was more accurate than the Friele model for wood color matching.

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

Cited by 9 publications

References 11 publications

Color matching of fiber blends: Stearns‐Noechel model of digital rotor spun yarn

Color matching of fiber blends: Stearns‐Noechel model of digital rotor spun yarn

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

Color spectra algorithm of hyperspectral wood dyeing using particle swarm optimization

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