A data-driven approach to traditional village colors: K-Means clustering of online images

Abstract

This study aims to quantify the color characteristics of traditional villages, explore the key aspects of color that attract tourist attention, and propose solutions to enhance the readability and legibility of these villages. The findings are intended to provide practical guidance for the restoration and use of village colors. The research focuses on how tourists perceive the color characteristics of traditional villages. The objective is to conduct color clustering analysis to identify the composition and characteristics of village colors, and further analyze the underlying causes to offer suggestions for optimization and enhancement. It employs a methodology based on urban imagery theory, using clustering and secondary extraction of color data from online images. The results reveal distinct contrasts and harmonies in the colors of the five elements providing a basis for improving spatial readability and visual guidance. These findings not only offer practical design references for optimizing traditional village colors but also provide valuable insights for the protection and restoration of other traditional sites. In particular, the contrast between the colors of boundaries and landmarks can enhance visual recognition, while the complementary color designs of paths and boundaries can improve spatial readability, contributing to the sustainable development of traditional villages.

Keywords

• color analysis
• k-means clustering
• web evaluation images
• city image theory
• daqitou village