The application of image recognition techniques in the realm of cultural heritage represents a significant advancement in preservation and analysis. However, existing scholarship on this topic has largely concentrated on specific methodologies and narrow categories, leaving a notable gap in broader understanding. This study aims to address this deficiency through a thorough bibliometric analysis of the Web of Science (WoS) literature from 1995 to 2024, integrating both qualitative and quantitative approaches to elucidate the macro-level evolution of the field. Our analysis reveals that the integration of artificial intelligence, particularly deep learning, has significantly enhanced digital documentation, artifact identification, and overall cultural heritage management. Looking forward, it is imperative that research endeavors expand the application of these techniques into multidisciplinary domains, including ecological monitoring and social policy. Additionally, this paper examines non-invasive identification methods for material classification and damage detection, highlighting the role of advanced modeling in optimizing the management of heritage sites. The emergence of keywords such as ‘ecosystem services’, ‘models’, and ‘energy’ in the recent literature underscores a shift toward sustainable practices in cultural heritage conservation. This trend reflects a growing recognition of the interconnectedness between heritage preservation and environmental sciences. The heightened awareness of environmental crises has, in turn, spurred the development of image recognition technologies tailored for cultural heritage applications. Prospective research in this field is anticipated to witness rapid advancements, particularly in real-time monitoring and community engagement, leading to the creation of more holistic tools for heritage conservation.

China’s Nationally Important Agricultural Heritage Systems (China-NIAHS) are agricultural systems with deep historical and cultural roots that exhibit temporal continuity and spatial heterogeneity in their formation and distribution. As modern and industrialized agriculture have developed, traditional agricultural systems are facing unprecedented challenges and pressures. This study investigates the spatiotemporal distribution and influencing factors of 196 China-NIAHS sites, categorized into five categories. Using spatial analysis techniques and Geographical Detectors, this study identifies key natural, socioeconomic, and cultural drivers shaping their distribution. The results reveal a predominantly clustered spatial distribution of China-NIAHS, centered around the Yangtze River Basin, with significant influences from population density, tourism development, and industrialization. Historical analysis highlights a west-to-east and northward migration of agricultural activity, driven by political stability and technological advancements. Further findings indicate that the spatial distribution of China-NIAHS is primarily determined by population density, tourism development, and river network density. Population density plays a pivotal role in heritage preservation, tourism development generates economic benefits and facilitates cultural dissemination, and river network density supports the formation and sustainability of heritage sites. Conversely, urbanization and economic development have limited influence, emphasizing the need to prioritize socioeconomic and natural factors in conservation strategies. This study provides a comprehensive understanding of the spatial and temporal dynamics of China-NIAHS, offering valuable insights for sustainable heritage conservation and the strategic integration of natural and socioeconomic factors into modern agricultural policies. These findings deepen the understanding of China-NIAHS, highlighting their role in ecological and cultural sustainability while supporting value assessment, region-specific protection, and sustainable utilization strategies.

After Buddhism spread to the Zhejiang, it underwent sinicization, giving rise to Chinese Buddhist architecture and forming a secularized character. The spatial-temporal distribution of historical Buddhist architecture in Zhejiang is strongly representative of Buddhist architecture. From the perspective of religious cultural geography, this study takes 11 prefecture-level cities of Zhejiang as the basic research units, and employs the spatial-analysis method of ArcGIS to analyze the spatial-temporal evolution characteristics of representative historical Buddhist architectural samples, and to explore the factors affecting their distribution. The research results indicate that the spatial distribution of representative historical Buddhist architectural samples in the Zhejiang is extensive, with a distinct single-core clustering characteristic. The mean-center movement of the representative historical Buddhist architectural samples in Zhejiang during different historical periods manifests in four distinct directional phases, overall moving from north to south. Natural, transportation, political, technological, economic, and religious cultural transmission factors collectively influence the spatial-temporal distribution of Buddhist architecture in Zhejiang. Especially the secularization of Buddhism and the syncretism of Confucianism, Daoism, and Buddhism have been the primary drivers in the spatial-temporal distribution evolution of Buddhist architecture.

Ancient Chinese embroidery is an important intangible part of the cultural heritage of mankind. Its colours and contours are a major source of oriental inspiration and design elements for designers today. This study presents an effective intelligent recognition of colour and contour based on K-means++ clustering and the Canny operator for colour and contour application of ancient Chinese embroidery images and for digital inheritance and innovation. First, digital cameras and portable scanners were used in embroidery image acquisition. Second, colour level adjustment, sharpening and smoothing were specially added to the preprocessing, because of the ancient embroidery age or colour errors caused by the shooting angle. Third, K-means++ clustering was used for colour clustering. Fourth, the Canny operator was used for contour detection. After the addition of colour level adjustment and sharpening in the preprocessing, the colours and contours could be acquired accurately and more effectively from embroidery images and be read and edited independently.

Taohuawu woodblock New Year prints are one of the most representative traditional multicolor woodblock print forms from the Jiangnan region of China and are recognized as an Intangible Cultural Heritage at the provincial level in Jiangsu. However, the development of mechanized and high-tech production methods, combined with the declining role of traditional festive customs in modern society, has posed significant challenges to the preservation and transmission of this art form. Existing digital preservation efforts mainly focus on two-dimensional scanning and archival storage, largely neglecting the essential processes of color separation and multicolor overprinting. In this study, a digital restoration method is proposed that integrates image processing, color clustering, and edge detection techniques for the efficient reconstruction of the traditional multicolor woodblock overprinting process. The approach applies the K-means++ clustering algorithm to extract the dominant colors and reconstruct individual color layers, in combination with CIELAB color space transformation to enhance color difference perception and improve segmentation accuracy. To address the uncertainty in determining the number of color layers, the elbow method, silhouette coefficient, and Calinski-Harabasz index are employed as clustering evaluation methods to identify the optimal number of clusters. The proposed approach enables the generation of complete, standardized digital color separations, providing a practical pathway for efficient reproduction and intelligent application of TWNY Prints, contributing to the digital preservation and innovative revitalization of intangible cultural heritage.

A silkworm deity was a Trade God worshipped by the court and the folk, and was also a spiritual symbol of sericulturists in medieval China. Images of the silkworm deity in ancient Chinese art are important relics of material heritage for studying culture and ritual activities in medieval China. This paper investigates images of silkworm worship from the Han Dynasty to the Yuan Dynasty to distinguish between their use by the court and the folk. This paper explores the gradual personification of the silkworm deity in medieval China, as well as the differences in the identity of the silkworm deity connected to the varying status of worshipers and the functions of the silkworm deity. It is proposed that silkworm deity worship is evidence of a tendency toward polytheism, and has a variety of identities and unified functions under the trend of continuous integration of three major religions and folk religion. The worship of the silkworm deity has the characteristics of hybridity, integrated and patriarchal, as well as the social edification and practical functionality caused by the different mentality of official and folk silkworm deity worship in medieval China.