Abstract: The optimization method of color matching design often faces convergence difficulties during the formation of the final scheme, because the designer’s evaluation usually enters an unstable state, which makes it difficult to accurately choose among the slightly different schemes. Thus, after the optimization method has completed the large-scale search, the final convergence stage generally still needs the designer to do the manual fine-tuning, which significantly lowers the efficiency of the whole optimization process. A non-random population generation technique based on continuous interpolation was developed for the convergence stage of interactive genetic algorithm to meet the demand of color image reproduction, which can assist designers to realize rapid fine-tuning and output the final design. A prototype system was developed based on graphic design software, in which two kinds of variation operations based on RGB and HSB color spaces and a multi-scheme fusion of crossover operation were given as three kinds of non-random population generation methods. It enabled designers to have a more intuitive visual perception on the color difference, to select schemes more quickly, and to improve the interactive experience of designers as users. The application is verified by the case of color matching design of e-sports chairs. 

Key words: color matching design, interactive optimization, non-random population