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Camouflage spots are mostly color patches of different colors. Compared with the traditional empirical color matching method, computer color matching can quickly and effectively calculate the proportion of red, yellow, and blue primary colors. In general, camouflage computer color matching in the practical application of the initial formula is not accurate and multiple color modification still cannot match. First, we measured the chroma coordinates of 98 standard swatches made of red, green, and blue coatings in different proportions by the OHSP-660 spectral reflectance tester. Then, we adopted polynomial regression algorithm by Statistical Product and Service Solutions (SPSS) to obtain the regression equation between [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text]. Finally, the fitting equation is used to obtain the paint color scheme in the coordinates of [Formula: see text], [Formula: see text], and [Formula: see text] in arbitrary uniform color space, so as to realize the purpose of computer color matching. The experimental results show that the minimum color difference is 1.691 ( L* a* b* unit) the maximum color difference is 2.497, which meets the design requirements of camouflage and target color difference being no more than 3. Our work provides a theoretical basis for the further development of computer color matching system in camouflage.

Computer color matching can improve production efficiency and reduce costs in color spun. However, in practice the computer color matching success rate for pre-colored fiber blends has not been good, leading to customers being unsatisfied with the accuracy of the color matching results. Aiming to improve the accuracy, a hybrid of least squares and grid search method has been proposed for spectrophotometric color matching of pre-colored fiber blend based on the improved Kubelka–Munk (K-M) double-constant theory. Two-primary, three-primary, four-primary, and five-primary pre-colored cotton fiber blends were prepared as standard samples to evaluate the color matching accuracy of the proposed method. Compared with the least squares method and the grid search method, the proposed method achieved better color matching effects and greatly shortened the calculation time, respectively. For 42 pre-colored fiber blends, the average color difference between the predicted results obtained by the proposed method, least squares method, and grid search method and the spectrophotometer measurements were respectively 0.29, 0.53, and 0.36 CIE2000 units. The experimental results indicated that the proposed method could predict the formulation of standard samples quickly and effectively, and that it was superior to other methods in providing satisfactory color matching results for the enterprises.

Color matching is necessary in the manufacture of colored fiber yarns, and its accuracy is one of the main goals in computer-aided color matching. A limited number of pre-colored fibers are blended to match the target color through predicted recipes. Of the color-prediction models applied in computer-aided color matching, two common ones, Stearns-Noechel and Friele, were selected to be modified to improve the color-prediction accuracy in this paper. The models were modified in three ways, in which the pending parameters in the models were determined through statistical analysis depending on median, wavelength, and components; thus, the Stearns-Noechel model was modified to Stearns-Noechel 1, Stearns-Noechel 2, and Stearns-Noechel 3, and the Friele model was modified to Friele 1, Friele 2, and Friele 3. The six modified models were affirmed through 261 colored fiber yarns prepared from five primary cotton fibers, including two-, three-, four-, and five-primary blends. The prediction results of 261 samples showed that Stearns-Noechel 3 had the highest accuracy among the modified Stearns-Noechel models, especially for four-primary blends with an average color difference of 0.50 Color Measurement Committee (CMC) (2:1) units, whereas Friele 1 had the highest accuracy among the modified Friele models, especially for five-primary blends with an average color difference of 0.46 CMC (2:1) units. These results indicate the modified model Stearns-Noechel 3 can be used in color prediction when there are fewer than five yarn components, and Friele 1 can be used for five components with lower color differences that better meet color-matching requirements in practical production.

Carrier dyeing is a method of dyeing polyester materials that is used when necessary. Although usage of carriers in dyeing enables the dyeing of polyester materials at atmospheric pressure, the undesirable properties of the carriers are drawbacks. Disperse dyes are classified under different energy levels and the dyeing methods and color and fastness properties of dyed materials are associated with this classification. Carriers can be used when dyeing at higher temperatures than 100°C to promote the leveling of the more difficult disperse dyes. In the presence of a carrier substance in the dye bath, the dyeing behavior of the disperse dyes may become sensitive to dyeing temperature and dye bath concentration changes. Disperse dyes may show distinct dyeing properties in combination dyeing in carrier dyeing although they belong to the same energy level. Color-matching operations made by using a color-matching software must take the sensitivity of both dye bath concentration and dyeing temperature of the disperse dyes into account in the carrier dyeing of polyester fibers. According to the experimental results obtained on individual disperse dyes in the present study, problems may arise in carrier dyeing of polyester fibers with disperse dyes in combination dyeing because of the different dyeing temperature and dye bath concentration sensitivity of dyes that have the same energy level. Combination dyeing must not be performed close to dyeing temperatures of 100°C when dyeing in the presence of a carrier.

Environmental and public health issues associated with dyes and their effluents are problematic areas for any dyehouse. If the toxicity and color of dyeing effluent can be predicted quantitatively before dyeing, one can select suitable dyes to reduce envi ronmental pollution. This study examines the acute toxicity of dyes and associated auxiliaries in terms of EC50, and these data are used to predict the toxicity of the dyeing effluent. The prediction accuracy is satisfactory when some statistical ap proaches, such as linear and nonlinear regression, are used. Furthermore, in order to make the toxicity data much easier to understand and much more directly comparable with each other, a toxicity index has been created according to the EC50 values in this study. Incorporating the toxicity information of the dyes with a computer color matching system permits the prediction of effluent toxicity generated by colorant recipes. This should assist colorists to select a "greener" formula while satisfying basic color quality requirements and will let colorists know well ahead of time the impact of toxicity from the effluent on the environment.

The process of dyeing of nylon with tertiary acid dye mixtures is controlled by automatic metering of dyes and chemicals. Closed-loop control is achieved by real-time data acquisition of the dyebath conditions coupled with a feedback control strategy. The objective of controlled dyeing is to obtain an on-tone build-up of shade using three monosulfonated acid dyes in mixture combinations. Computerized dosing pumps control the pH, the dyebath concentrations of the individual dyes, and the total sorption of each dye during the process. Photographs of yarn cross sections examined under the polarizing microscope reveal uniform penetration of dye in the individual fibers of the yarns. Color matching of samples dyed under identical dyeing conditions shows good shade reproducibility. It is also possible to re-use a dyebath of residual dyes and chemicals from a previous dyeing. Thus, good shade reproducibility and uniform shade build-up can be achieved in a laboratory dyeing machine by adopting real-time closed-loop control.

Some suggestions are presented in this paper for optimizing color matching in blends of pre-colored fibers. The proposed algorithm suggests an initial spectrophotometric trial for color matching with all selected colored fibers. If the initial spectrophotometric match does not satisfy the colorimetric conditions, the data will be applied in a later colorimetric attempt. In that attempt, by applying the pseudoinverse algorithm in the iterative process, it is not necessary to limit the number of colored fibers to four, as Allen suggested for the two-constant theory.