The work aims to externalize and quantitatively describe the user's implicit color image perception, reduce the error of color scheme evaluation result caused by multi-index weight blur, and maintain the consistency of design and evaluation principles. A color matching design and scheme evaluation method combining factor analysis-entropy weight method and multi-criterion compromise solution ranking was proposed. The Delphi method and other methods were used to establish a target color image vocabulary set and the representative alternative dominant color sample library was obtained from the RGB parameter range by setting equidistant intervals. The semantic difference method was used to construct the evaluation matrix, the factor analysis was carried out to extract the color factors, the color image scoring model was obtained by combining the entropy weight method, and the color samples were scored and ranked to obtain the alternative dominant color library. Based on hue distance theory, the auxiliary color selection principle was formed. According to the index-empowered VIKOR method, multiple alternatives were evaluated and reasonable ranking results were obtained. The color matching design and scheme evaluation of a certain type of wheel loader are verified by example, and the results show that this research method fully considers the amount of information of each index when evaluating multiple color matching schemes, which helps designers to dig deep into the potential color needs of users.