Abstract:

Objective Shaded weaves are extensively used in the design of figured full-color simulation of jacquard fabrics, to the extent that this design pattern is solidified into a certain mind-set. In order to overcome this situation, a design method of multi-color dot superposition combination is proposed for motivating the diversified development of the design technology for color simulation jacquard fabrics.

Method The digital screen technology was adopted to discretize the digital color image with continuous tone into a multi-color dot image, which directly became the weave structure of a jacquard fabric. The multi-color dot image was composed of no more than 6 to 8 fixed colors (Fig. 1(b)). In order to investigate the color simulation performance of jacquard fabrics based on multi-color dot image, six jacquard fabric samples were woven by using two design method respectively for representing three different pictures (Fig. 3). Three color measurement point templates were designed for collecting the color data of the jacquard fabric samples (Fig. 4). The templates were fixed on the jacquard fabrics, and then the Lab values of each color measurement point were measured by using the American X-rite Color i7 desktop spectrophotometer. By comparative analyzing the color difference between the images of jacquard fabric samples and the original images, the color simulation performances of the jacquard fabric applying the multi-color dot image were demonstrated.

Results The average total color differences (ΔE_ab) among the six jacquard fabric samples and the corresponding original image were calculated (Tab. 2). The data of three multi-color dot structure jacquard fabrics was 14.31, 24.09 and 16.10, representing improved color simulation performance of 13.11%, 19.49% and 4.28% over that of shaded weave jacquard fabric images, respectively. In addition to comparing the total color difference of single jacquard fabrics, the measured color data of six jacquard fabrics were classified into two groups according to the two different design method of multi-color dot images and shaded weaves, and then comparatively analyzed in terms of lightness, total color difference, red value, green value, yellow value and blue value (Tab. 3). The six terms of color difference data of multi-color dot jacquard fabrics were reduced in varying degrees comparing with that of shaded weave jacquard fabrics. At last, the ΔE_ab between the color measurement points of the original images and the multi-color dot images were taken as the dependent variable, and the lightness, red-green value and yellow-blue value of all the color measurement points of the three original images were taken as the independent variables. The polynomial regression equation was used for fitting, the results (Fig. 6 and 7) showed that the color simulation effect of multi-color dot jacquard fabric was better for neutral color, medium brightness color and low saturation color, while the simulation effect of vivid, bright or extremely dark color was relatively not so well.

Conclusion According to the comparative investigations of the color differences of the images of the multi-color dot structure jacquard fabrics and that of the shaded weave jacquard fabrics, it proves that the jacquard fabrics by using the method of discretizing the continuous tone color image into a multi-color dot image can improve the color simulation performance. Because the color number of image is significantly reduced without obvious affecting the image color quality, the large number of fabric weaves are no longer needed, which realizes overcoming the limitations of fabric weave in color simulation and provides a new way for the design of color simulation jacquard fabrics. For expressing image color, the jacquard fabrics depend upon the design factor of weave but excessive reliance on the weave would also have a negative impact on the expression of image color, which is also worth thinking about.

Key words: multi-color dot, jacquard fabric, color simulation, design mode, color difference, simulation evaluation