ESEARCH ON THE CONSTRUCTION OF COLOR SYSTEM FOR WUHAN HISTORIC CITY BASED ON K-MEANS ALGORITHM AND PCCS SYSTEM

Abstract

Objective: To address the problems of chaotic color elements, conflicts between old and new interfaces, and ambiguous regional semantics during Wuhan’s urban renewal, this study constructs a dynamic and quantifiable urban color management system^[1]. Methods: A two-stage K-means clustering combined with PCCS semantic mapping is employed. Based on 151 local chronicle records and 112 valid image samples, colors are extracted in HSV space^[2]. The silhouette coefficient determines the optimal K=10, and after secondary clustering, 25 core colors are obtained, followed by standardized conversion from HSV to PCCS and semantic assignment. Results: A three-level color system consisting of primary, secondary, and accent colors is established. Integrated with Wuhan’s threetown geographic layout and historical context, a governance framework with spatiotemporal distribution and semantic association is constructed. Conclusion: Questionnaire validation shows good public acceptance, providing a reusable technical pathway for digital color management of historic cities^[3].