Applied Mathematics and Nonlinear Sciences
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Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 9, Issue 1


Published
on

January 31, 2024


Pages


DOI

Article

Research on Digital Image Record in Intangible Cultural Heritage Inheritance Innovation under the Background of Big Data

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Authors

Nai Li Affiliation:
Art Internation School of Design, University of Sanya, Sanya, Hainan, 523808, China.


Abstract

The purpose of this paper is to investigate the digital lens presentation effect and image dissemination effect of intangible cultural heritage. In order to test the lens boundary detection technology of ICH digital images, we focus on analyzing the number of image frames, the number of mutations and the number of gradual changes of ICH characters, space-time and events, and exploring the checking completeness, the checking accuracy and the comprehensive detection rate of this paper’s algorithm and the dual-threshold comparative method on different types of ICH image fragments. Combined with the descriptive analysis of valid samples, we explore the main types of transmission of NRM digital images and clarify the degree of media utilization and the ranking of transmission power of NRM digital images in the Yangtze River Delta region. Shanghai has the strongest online dissemination power of traditional theater, traditional fine arts and traditional arts and crafts, with 1284586, 310468, and 237818, respectively, while traditional music, Chinese opera and folklore have the weakest dissemination power in Shanghai. Traditional music makes up 18.73% of them. To ensure non-heritage culture’s inheritance, it is necessary to strengthen the use of digital imaging technology to achieve linkage communication between non-heritage cultures and build an overall communication system.


Keywords

Lens boundary detection, Double threshold comparison method, Digital imaging, Non-heritage, 93C62


Citation

Li, N. (2024). Research on digital image record in intangible cultural heritage inheritance innovation under the background of big data. Applied Mathematics and Nonlinear Sciences, 9(1). https://doi.org/10.2478/amns-2024-0067
2 Total citations
2.46 FWCI
2 Recent citations
(2 years)
10 References
Open Access Yes
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Published by: Engineering Journals

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