From photographic images to hierarchical networks―Color associations of a traditional Chinese garden

Abstract The complexity of the environment and the richness of landscape color make it difficult to objectively measure color in gardens. However, with the use of machine vision and image processing algorithms, it is now possible to accurately quantify the colors of the built environment through photo recognition, classification, enhancement, and segmentation. This approach can produce correlation intensity charts and hierarchical networks that illustrate theme colors and their associations. To explore this methodology, we have selected Beijing Xiangshan Temple―a traditional Chinese garden and temple with rich landscape colors―as the research object. Using a combination of machine vision image processing technology and color clustering algorithms, we aim to establish a landscape color analysis model based on the Munsell color system and color harmony theory. Ultimately, this will provide a quantifiable and objective reference basis for the design and repair of temple garden colors, with a view to achieving the inheritance and development of classical gardens.