Extraction and Application of Color Genes of Brand Leather Goods based on K-Means Clustering Algorithm

Color is one of the elements of leather goods brand construction. Extracting the color genes of well-known brands and learning the construct methods of their color systems can serve as references for the innovative design of leather goods. Based on the K-Means clustering algorithm and the superimposed computer unsupervised self-learning, the colors of the main products and show products of the brand leather goods were independently identified and classified into color clusters. This paper extracted the color genes of the brand leather goods, analyzed the color usage rules of the brand leather goods, and built an intuitive color network model. And according to the requirements of innovative design, the extracted colors were automatically assigned to leather goods products, which can provide a reference for the color design of leather goods products.