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<p>Cultural heritage is a response to the characteristics of a society and deserves to be protected and passed on to future generations, but there is still a lack of knowledge and skills related to it in the methodology of digital preservation of intangible cultural heritage. This paper aims to digitally preserve intangible cultural heritage in Shaanxi by utilizing methods such as feature point description, image edge detection, and visual feature extraction. The scale space expression algorithm is applied to keep the feature point scale of the intangible cultural heritage unchanged, and the scale space of the image is obtained by convolving the Gaussian convolution kernel with the image. The Sobel operator is employed to evaluate the significance of pixels in the non-heritage image to identify the edge effect of the image. Focusing on analyzing the digitization types of Shaanxi’s non-legacy, we explored the role of images in the protection of non-legacy and formulated the dissemination path of Internet+Non-legacy for the current situation of Shaanxi’s non-legacy. The results show that among the 12 NHs in Shaanxi, the number of textual materials is the largest, accounting for 43.33% of all digital materials, followed by the proportion of images at 33.33%, and the current digitization of NHs needs the supplementation of audiovisual materials the most, with audiovisual materials accounting for only 23.33%. The value of images for the protection of non-heritage cultural heritage reflects the non-heritage characteristics intuitively, and the range of Shaanxi non-heritage image dissemination index is in the range of 21-89 interval, and with the change of time, people pay more and more attention to Shaanxi non-heritage.</p>
</abstract>

Cultural heritage is a response to the characteristics of a society and deserves to be protected and passed on to future generations, but there is still a lack of knowledge and skills related to it in the methodology of digital preservation of intangible cultural heritage. This paper aims to digitally preserve intangible cultural heritage in Shaanxi by utilizing methods such as feature point description, image edge detection, and visual feature extraction. The scale space expression algorithm is applied to keep the feature point scale of the intangible cultural heritage unchanged, and the scale space of the image is obtained by convolving the Gaussian convolution kernel with the image. The Sobel operator is employed to evaluate the significance of pixels in the non-heritage image to identify the edge effect of the image. Focusing on analyzing the digitization types of Shaanxi’s non-legacy, we explored the role of images in the protection of non-legacy and formulated the dissemination path of Internet+Non-legacy for the current situation of Shaanxi’s non-legacy. The results show that among the 12 NHs in Shaanxi, the number of textual materials is the largest, accounting for 43.33% of all digital materials, followed by the proportion of images at 33.33%, and the current digitization of NHs needs the supplementation of audiovisual materials the most, with audiovisual materials accounting for only 23.33%. The value of images for the protection of non-heritage cultural heritage reflects the non-heritage characteristics intuitively, and the range of Shaanxi non-heritage image dissemination index is in the range of 21-89 interval, and with the change of time, people pay more and more attention to Shaanxi non-heritage.

Research on the Protection and Dissemination of Intangible Cultural Heritage with Regional Cultural Characteristics in Shaanxi under the Background of Big Data

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

Cultural heritage is a response to the characteristics of a society and deserves to be protected and passed on to future generations, but there is still a lack...

Research on the Protection and Dissemination of Intangible Cultural Heritage with Regional Cultural Characteristics in Shaanxi under the Background of Big Data

Online veröffentlicht: 31. Jan. 2024

Seitenbereich: -

Eingereicht: 15. Dez. 2023

Akzeptiert: 21. Dez. 2023

DOI: https://doi.org/10.2478/amns-2024-0102

Schlüsselwörter
Feature point description, Image edge detection, Visual feature extraction, Non-heritage protection

© 2024 Xinglu Wang, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Research on the Protection and Dissemination of Intangible Cultural Heritage with Regional Cultural Characteristics in Shaanxi under the Background of Big Data

Online veröffentlicht: 31. Jan. 2024

Seitenbereich: -

Eingereicht: 15. Dez. 2023

Akzeptiert: 21. Dez. 2023

DOI: https://doi.org/10.2478/amns-2024-0102

SchlüsselwörterFeature point description, Image edge detection, Visual feature extraction, Non-heritage protection

© 2024 Xinglu Wang, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Feature point description, Image edge detection, Visual feature extraction, Non-heritage protection