Rockeries are unique elements of Chinese classical gardens with historical, cultural, artistic, and scientific value. One of the essential characteristics of garden rockery is the cave features since cave morphological features determine the degree of “Tou” (riddled through) and “Lou” (hollowed out well) features as the defined by rockery appreciation theory, which is important for rockery heritage conservation, assessment, and management. However, in heritage studies, accurately identifying and evaluating rockery caves is a difficult task because of a cave's irregular shape. This paper proposes a methodology to extract and classify cave features by point clouds obtained from data using a handheld laser scanner with a camera. Without completing surface reconstruction, the rockery point cloud is first sliced into chips, then cave chips were extracted from these approximately two-dimensional chips and next merged to obtain three-dimensional cave point clouds. Finally, the cave boundary points are extracted from the cave and fitted by an ellipse for classification. To extract and classify cave features, a methodology to improve rockery digitalization quality is also proposed. The raw point cloud data were preprocessed by pose adjustment, noise removal, and hole repair. The experimental results for the two rockeries in Tongji University and Qiuxiapu Garden indicate that the improved digitization scheme generates complete and closed rockery point clouds, all types of caves were effectively extracted and classified by our proposed method. Additionally, the extracted caves are still represented by point clouds, which suggest the possibility for other research in the future.

The Rockery is often a key element of a Classical Chinese Garden. It’s exquisite detailed physical characteristics a major contributor to artistic value, aesthetic appeal, and the carrier of historical and cultural heritage values. Poets and scholars have often described the beauty of these places in classical gardens in qualitative terms but lacked the quantitative tools to provide replicable metric descriptions. The highly complex forms and surfaces, irregularity, and fragility of garden rockeries has challenged authors to accurately describe the characteristics of these qualities using traditional methods and tools. This article presents a new method of digital characterization approach based on laser scanning and point cloud visualization, which can quantitatively detect and represent the pattern of rockery surface textures. It offers a replicable accurate quantitative descriptor of the Classical Chinese rockery. The Small-Rock Mountain Retreat, a nationally protected rockery garden in China, has been used as a case study. It contains original historic elements and more recently restored areas. Two characteristics of rockery surfaces, including the well-proportioned density and space, and the proper contrast between solid and void, were analyzed by examining four attributes: (1) surface complexity; (2) contour curvature; (3) shape variation; and (4) the interweaving of lightness and darkness. The findings demonstrate that, despite some similarities between the restored portion of the rockery and the historical remnants, there are variances in the richness of the details and the balanced distribution of shape change. The digital characterization approach introduced in this article offers a new perspective for recording and in turn safeguarding Chinese garden rockeries and other irregular cultural heritage objects.