Collaborative k-means clustering and color transfer algorithm for intelligent color scheme generation in clothing design

With the continuous development of computer technology, the field of fashion design increasingly emphasizes intelligence and personalization. A research has proposed an intelligent color scheme generation tool for clothing design based on K-means clustering and color transfer algorithm, aiming to improve the color matching effect and meet the personal style needs of modern consumers by optimizing the color extraction and transfer process. This article analyzes the shortcomings of current clothing design color matching tools and points out the limitations of existing systems in color extraction and application. Simulation results showed that this method can effectively extract color features and has good feasibility. By applying color transfer algorithms to different images, simulation results demonstrate the advantages of this method in terms of color consistency and visual effects. This article designs and implements an intelligent color matching system for clothing design, introducing the overall process of the color matching system, the structure of the color transfer module, and the establishment of the color matching model. After a series of tests, this tool has demonstrated efficient color matching capabilities in practical applications, meeting the diverse needs of designers for color matching.