Methods for Predicting Spectral Response of Fibers Blends
Textile companies usually manufacture fabrics using a mix of pre-colored fibers according to a traditional recipe based on their own experience. Unfortunately, mainly due to the fibers dyeing process, the colorimetric distance between the obtained fabric and the desired one results unsatisfactory with respect to a colorimetric threshold established by the technicians. In such cases, colorists are required to slightly change the original recipe in order to reduce the colorimetric distance. This trial and error process is time-consuming and requires the work of highly skilled operators. Computer-based color recipe assessment methods have been proposed so far in scientific literature to address this issue. Unlikely, many methods are still far to be reliably predictive when the fabric is composed by a high number of components. Accordingly, the present work proposes two alternative methods based on Kubelka-Munk and subtractive mixing able to perform a reliable prediction of the spectrophotometric response of a fabric obtained by means of any variation of a recipe. The assessment performed on a prototypal implementation of the two methods demonstrates that they are suitable for reliable prediction of fabric blends spectral response.
KeywordsComputer-based color assessment Kubelka-Munk theory Spectro-photometer Fabric blend
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