Research on the extraction of inscription rubbings information of stone carved cultural relics based on 3D fine models

Rubbings are essential for documenting the geometric features of inscriptions on cultural relics and represent an enduring art form. With the refinement of artifact preservation laws and the accelerated pace of cultural relic digitization, digital rubbing technology now offers a non-contact means of capturing the geometric characteristics of inscriptions on cultural relics. Current algorithms for generating digital rubbings from two-dimensional (2D) images and three-dimensional (3D) depth data are inadequate for complex surfaces, particularly stone carving cultural relics. To address the aforementioned issues, this paper proposes a method for extracting digital rubbing information from 3D digital models of cultural relics. First, the Root Mean Squared Error (RMSE)-constrained smoothing algorithm is used to obtain the optimal fitting surface; next, collision detection is employed to acquire the depth information of the model’s vertices; then, a nonlinear function is used for grayscale mapping; finally, the grayscale information is applied to the model vertices, generating measurable digital rubbing textures on the corresponding surfaces of the digital relic model. This method extracts rubbing information on fine 3D models. Experiments demonstrate its feasibility and effectiveness in the acquisition of depth reference surface, depth calculation, and the presentation of rubbing information. Compared to traditional methods, rubbing extraction based on 3D models produces undistorted, measurable, and realistic digital rubbings, providing significant research value and practical significance.

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Publication Details

Journal
npj Heritage Science
Published
2025-02-24
DOI
https://doi.org/10.1038/s40494-025-01610-4
Citations
2
Primary Topic
Image Processing and 3D Reconstruction
Type
article
Field-Weighted Citation Impact
2.55

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article

Research on the extraction of inscription rubbings information of stone carved cultural relics based on 3D fine models

Xinjian Ma, Guangshu Xia, Yang Wang, Chunmei Hu et al.
2 citations
npj Heritage Science
Image Processing and 3D Reconstruction
2.55
article

Research on the extraction of inscription rubbings information of stone carved cultural relics based on 3D fine models

Xinjian Ma, Guangshu Xia, Yang Wang, Chunmei Hu, Yang Han
article en
2 citations

Abstract

Rubbings are essential for documenting the geometric features of inscriptions on cultural relics and represent an enduring art form. With the refinement of artifact preservation laws and the accelerated pace of cultural relic digitization, digital rubbing technology now offers a non-contact means of capturing the geometric characteristics of inscriptions on cultural relics. Current algorithms for generating digital rubbings from two-dimensional (2D) images and three-dimensional (3D) depth data are inadequate for complex surfaces, particularly stone carving cultural relics. To address the aforementioned issues, this paper proposes a method for extracting digital rubbing information from 3D digital models of cultural relics. First, the Root Mean Squared Error (RMSE)-constrained smoothing algorithm is used to obtain the optimal fitting surface; next, collision detection is employed to acquire the depth information of the model’s vertices; then, a nonlinear function is used for grayscale mapping; finally, the grayscale information is applied to the model vertices, generating measurable digital rubbing textures on the corresponding surfaces of the digital relic model. This method extracts rubbing information on fine 3D models. Experiments demonstrate its feasibility and effectiveness in the acquisition of depth reference surface, depth calculation, and the presentation of rubbing information. Compared to traditional methods, rubbing extraction based on 3D models produces undistorted, measurable, and realistic digital rubbings, providing significant research value and practical significance.

npj Heritage ScienceVol. 13(1)
Cultural Relics Institute Hebei Province (CN), Chinese Academy of Surveying and Mapping (CN), Beijing University of Civil Engineering and Architecture (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 12%
Image Processing and 3D Reconstruction
2.55
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