Research Article
An Information Hiding Algorithm Based on Multi-carrier Fusion State Partitioning of 3D Models
@INPROCEEDINGS{10.1007/978-3-031-56580-9_10, author={Shuai Ren and Bo Li and Shengxia Liu}, title={An Information Hiding Algorithm Based on Multi-carrier Fusion State Partitioning of 3D Models}, proceedings={Digital Forensics and Cyber Crime. 14th EAI International Conference, ICDF2C 2023, New York City, NY, USA, November 30, 2023, Proceedings, Part I}, proceedings_a={ICDF2C}, year={2024}, month={4}, keywords={Information Hiding 3D Models Multi-carriers 3D Fused State Models}, doi={10.1007/978-3-031-56580-9_10} }- Shuai Ren
Bo Li
Shengxia Liu
Year: 2024
An Information Hiding Algorithm Based on Multi-carrier Fusion State Partitioning of 3D Models
ICDF2C
Springer
DOI: 10.1007/978-3-031-56580-9_10
Abstract
Aiming at the shortcomings of existing single-vector 3D model information hiding algorithms in terms of capacity, robustness and invisibility, this paper proposes an information hiding algorithm based on multi-carrier fusion state partitioning of 3D models. Firstly, multiple three-dimensional vectors to be hidden are fused according to the radial distance between the center of each model and the inner tangential sphere, and then the inner tangential sphere of the fusion body is determined, and the fusion model is divided into inner and outer parts. Then, using the rectangular coordinate plane of space and the inner tangent sphere, the fused point cloud is divided into 16 point cloud model blocks, and the feature points in the subregion space are extracted. In the inner and outer regions of the inner tangent sphere, the two significant points with the lowest coordinate values of the three feature points are selected as the feature areas for hidden data embedding. The hidden data is scrambled by the knight parade method to obtain the corresponding binary coded sequence. Finally, the hidden data is embedded by matching and modifying the parity sequence of the two significant bits with the lowest coordinate values of the feature vertices. The simulation results show that the proposed algorithm has good robustness and invisibility.
