Quantitative contrast of urban agglomeration colors based on image clustering algorithm: Case study of the Xia-Zhang-Quan metropolitan area

Abstract

Color is an important element to consider when shaping urban characteristics. However, previous studies seldom included quantitative analyses of color relationships between urban agglomerations within proximal regions and with similar cultures to distinguish and shape individual urban personalities. This study focused on Xiamen, Zhangzhou, and Quanzhou metropolitan areas, which are influenced by Minnan culture, and collected natural and cultural landscape network images that collectively represent the urban landscape in China. Color extraction, computer vision processing technologies, and clustering algorithms, such as k-means partitioning, hierarchical methods, and co-occurrence frequency, were applied using image recognition. We then established an urban color database and quantified color attributes. Finally, we conducted a comparative analysis of dominant colors and color combination associations in Xiamen, Zhangzhou, and Quanzhou metropolitan areas to explore their similarities and differences and define their characteristics. We also considered other cities of the same type for comparison.

Keywords

• City color
• Urban agglomeration
• Network image
• Clustering algorithm
• Computer vision