The authors present a fully automatic method of color theme extraction and transfer for fabric color design. For real-life fabrics, such extraction and transfer is performed through a highly time consuming and knowledge intensive process, known as color theme design. Specifically color and tone style adjustments are part of a generic process of cognition involved in the creation of new fabric designs. The authors explicitly formalize the process of color theme extraction from a set of images as a process of color mood based hierarchical data clustering and optimization. They begin with image sorting within a cognitive theme and color compatibility learning from large datasets. They then propose fully automatic color-texture association and color transfer algorithms which satisfy the criteria used in professional fabric pattern design while ensuring the plausibility of the cognitive theme preserved color transfer from the images to fabric patterns. Lastly, the color transfer process is formulated as a constrained optimization problem that is solved efficiently by total variation minimization. The use of color theme associations can automatically generate new fabric designs that rival complex commercial designs that are otherwise difficult to generate even by experienced designers. The authors’ fully automatic color theme preserving transfer method leads to a new approach to fabric design that significantly save time and cost for both fashion designers and computer artists.
|Number of pages
|International journal of software science and computational intelligence
|Published - 2012