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|Title:||Color and color appearance prediction for jacquard woven fabrics||Authors:||Chae, Youngjoo||Advisors:||Xin, John H. (ITC)
Hua, Tao (ITC)
Color in the textile industries.
|Issue Date:||2016||Publisher:||The Hong Kong Polytechnic University||Abstract:||Jacquard weaving affords the opportunity to design a huge number of color and intricate pattern effects which cannot be matched by any other weaving technique. In particular, the final color appearance of woven structures is the key element of Jacquard fabric design, which is the result of both combined weave-color effects achieved from a series of different colored yarns interlaced in varying proportions, and neighboring color effect in multi-colored fabrics. In this study, the color appearance design for Jacquard woven fabrics, in geometric and colorimetric aspects, and its numerical modeling was performed. Two main research works were conducted: (1) optimized physical color prediction of single-colored Jacquard fabrics and (2) perceived color appearance modeling of multi-colored Jacquard fabrics. Eighty-four single-colored Jacquard fabrics were designed first based on the principle of optically subtractive color mixing with the use of CMY subtractive primaries, that is, cyan, magenta, and yellow yarns, in four different weave structures. Then, by applying the six color prediction models previously developed for color mixing, the physical color attributes of the 84 fabrics were predicted from the structural details of the fabrics and the physically measured colors of the individual yarns used. The performance of the models was evaluated by calculating the difference between the predicted and the measured fabric colors, using ΔECMC(2:1). As a result, the average color difference was 12 ΔECMC(2:1) units, which is quite high to be accepted in the textile industry. To improve the prediction accuracy, all six models were numerically optimized and, as a result, the accuracy was substantially improved in physical color predictions with the ΔECMC(2:1) to 4.83 units on average. Among the six optimized models, the optimized W-O (Warburton-Oliver) model was found to be the most accurate model having the lowest average ΔECMC(2:1) of approximately 2. This indicates the potential usefulness of the color prediction model when being applied to the current digital process of Jacquard production using computer-aided design (CAD) systems.
For color appearance modeling of multi-colored Jacquard fabrics with the consideration of neighboring color effects, 240 Jacquard woven color combinations were designed and constructed. In the color combinations, each of CMY primary colors was placed with 20 different neighboring colors in varying proportions in striped paradigms. The three primary colors were then visually assessed by 12 normal color-vision observers using the magnitude estimation method estimating their lightness L*, colorfulness C*, and hue h° values through the comparison with reference samples consisting solely of each primary color. Based on the visual estimates, the effects of the size and physical color attributes of neighboring colors on the perception of primary colors were statistically analyzed. The significant neighboring color effects found in this study were: size, lightness, colorfulness, and hue on lightness perception; colorfulness and hue on colorfulness perception; and hue on hue perception. Finally, with the use of these significant variables of neighboring colors, a color appearance model predicting the perceived lightness, colorfulness, and hue for woven color combinations was developed. The success of its color appearance predictions was evaluated by calculating the difference between the predicted and the previously estimated color appearance values, and as a result, there was an excellent agreement showing 2.49 ΔECMC(2:1) on average, with the average variation of ΔL*, ΔC*, and Δh° . equal to 0.94, 0.98, and 3.96, respectively. This study is believed to provide more advantageous methodologies to design and produce Jacquard woven fabrics in desired color appearances by using the color prediction model and the color appearance model developed. In addition, the findings in this study would be an important theoretical basis for the further development of the color appearance prediction of the more complex combination of colors and patterns.
|Description:||PolyU Library Call No.: [THS] LG51 .H577P ITC 2016 Chae
xix, 218 pages :color illustrations
|URI:||http://hdl.handle.net/10397/53703||Rights:||All rights reserved.|
|Appears in Collections:||Thesis|
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