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基于K均值聚类算法的品牌皮具色彩基因提取与应用

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

  • 摘要: 色彩是皮具品牌构建的要素之一,对知名品牌的色彩基因进行提取,学习其色彩体系的构建方法,可以作为皮具创新设计的参考。基于K均值聚类算法,叠加计算机无监督学习,对品牌皮具的主要产品、秀场产品的颜色进行自主的识别和色簇归类,提取出品牌皮具的色彩基因,分析品牌的用色规律,构建直观的色彩网络模型。并根据创新设计的需求,将提取出的色彩自动赋色到皮具产品中,可以为皮具产品色彩设计提供参考。

     

    Abstract: 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.

     

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