Multi-carrier information hiding algorithm based on three-dimensional model’s concave-convex structure characteristics

Shuai REN; Lei SHI; Binbin WANG; Huirong CHENG; Qianqian ZHANG; Honglin LIU

doi:10.11959/j.issn.1000-0801.2022008

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Multi-carrier information hiding algorithm based on three-dimensional model’s concave-convex structure characteristics

Research and Development | 更新时间：2024-06-05

- Multi-carrier information hiding algorithm based on three-dimensional model’s concave-convex structure characteristics
- Telecommunications Science Vol. 38, Issue 2, Pages: 59-70(2022)
- 作者机构：
  
  1. 长安大学信息工程学院，陕西西安 710064
  2. 桂林航天工业学院，广西桂林 541004
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.1000-0801.2022008
  CLC： TP309
- Published Online：2022-02，
  
  Published：20 February 2022
- 稿件说明：
移动端阅览
Shuai REN, Lei SHI, Binbin WANG, et al. Multi-carrier information hiding algorithm based on three-dimensional model’s concave-convex structure characteristics[J]. Telecommunications science, 2022, 38(2): 59-70.
DOI：

Shuai REN, Lei SHI, Binbin WANG, et al. Multi-carrier information hiding algorithm based on three-dimensional model’s concave-convex structure characteristics[J]. Telecommunications science, 2022, 38(2): 59-70. DOI： 10.11959/j.issn.1000-0801.2022008.

摘要

针对单载体的信息隐藏算法的嵌入容量、不可见性和鲁棒性受载体数量限制无法进一步提升的问题，将载体体素化和秘密信息的嵌入结合三维模型凹凸结构特征，提出了一种基于三维模型凹凸结构特征的多载体信息隐藏算法。首先，对三维模型进行体素化，并根据体素化后获得的数据集提取三维模型的凹凸结构特征对载体库进行分类，转换得到凹凸度区间后对其编码；其次，根据载体分类数对秘密信息分段并进行置乱和优化，使载体和秘密信息的嵌入通过其分类及分段数有效地联系起来，分别通过凹凸度区间和体素化坐标点的编码数据双重嵌入秘密信息，进一步提升算法性能；最后，应用遗传算法对秘密信息进行最优调整后完成信息隐藏。实验表明，与基于单载体的高容量三维模型隐写算法相比，算法的不可见性、鲁棒性和容量性都有明显提升。

Abstract

Aiming at the problem that the embedding capacity

invaibility and robustness of a single-carrier information hiding algorithm cannot be further improved due to the limitation of the number of carriers

the voxelization of the carrier and the embedding of secret information were combined with the concave-convex structure characteristics of the three-dimensional model

and a method was proposed.A multi-carrier information hiding algorithm based on the three-dimensional model’s concave-convex structure features.Firstly

the three-dimensional model was voxelized

and the three-dimensional model’s concave-convex structure features were extracted from the data set obtained after voxelization to classify the carrier library

and the concave-convex degree was obtained by conversion after the interval was encoded.Secondly

the secret information was segmented according to the number of carrier classifications and scrambled and optimized

so that the embedding of the carrier and the secret information was effectively connected through its classification and number of segments

and double embedding of secret information by encoding data of concavity intervals and voxelized coordinate points

respectively

to further improve the performance of the algorithm.Finally

the genetic algorithm was applied to optimize the secret information to complete the information hiding.The experiment shows that compared with the high-capacity three-dimensional model steganography algorithm based on a single carrier

the invisibility

robustness and capacity of the algorithm were significantly improved.

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Keywords

references

任帅 , 王震 , 徐振超 , 等 . 一种基于 OBJ 三维模型纹理贴图的信息隐藏算法 [J ] . 北京邮电大学学报 , 2019 , 42 ( 1 ): 22 - 27 .

REN S , WANG Z , XU Z C , et al . Information hiding scheme based on texture mapping of 3D model in OBJ format [J ] . Journal of Beijing University of Posts and Telecommunications , 2019 , 42 ( 1 ): 22 - 27 .

张启龙 , 温涛 , 宋晓莹 , 等 . 基于自适应直方图修改的网格可逆信息隐藏 [J ] . 东北大学学报(自然科学版) , 2020 , 41 ( 3 ): 316 - 320 , 360 .

ZHANG Q L , WEN T , SONG X Y , et al . Reversible data hiding algorithm based on adaptive histogram modification for 3D mesh models [J ] . Journal of Northeastern University (Natural Science) , 2020 , 41 ( 3 ): 316 - 320 , 360 .

ZHOU H , CHEN K J , ZHANG W M , et al . Distortion design for secure adaptive 3-D mesh steganography [J ] . IEEE Transactions on Multimedia , 2019 , 21 ( 6 ): 1384 - 1398 .

TSAI Y Y . Separable reversible data hiding for encrypted three-dimensional models based on spatial subdivision and space encoding [J ] . IEEE Transactions on Multimedia , 2021 ( 23 ): 2286 - 2296 .

WANG P S , LIU Y , GUO Y X , et al . O-CNN:Octree-based convolutional neural networks for 3D shape analysis [J ] . ACM Transactions on Graphics , 2017 , 36 ( 4 ): 72 .

KER A D , . Batch steganography and pooled steganalysis [C ] // IH'06:Proceedings of the 8th International Conference on Information Hiding , 2006 : 265 - 281 .

张新鹏 , 钱振兴 , 李晟 . 信息隐藏研究展望 [J ] . 应用科学学报 , 2016 , 34 ( 5 ): 475 - 489 .

ZHANG X P , QIAN Z X , LI S . Prospect of digital steganography research [J ] . Journal of Applied Sciences , 2016 , 34 ( 5 ): 475 - 489 .

任帅 , 王震 , 苏东旭 , 等 . 基于三维模型贴图与结构数据的信息隐藏算法 [J ] . 通信学报 , 2019 , 40 ( 5 ): 211 - 222 .

REN S , WANG Z , SU D X , et al . Information hiding algorithm based on mapping and structure data of 3D model [J ] . Journal on Communications , 2019 , 40 ( 5 ): 211 - 222 .

任帅 , 徐振超 , 王震 , 等 . 基于多融合态的低密度三维模型信息隐藏算法 [J ] . 计算机应用 , 2019 , 39 ( 4 ): 1100 - 1105 .

REN S , XU Z C , WANG Z , et al . Low-density 3D model information hiding algorithm based on multple fusion states [J ] . Journal of Computer Applications , 2019 , 39 ( 4 ): 1100 - 1105 .

张满囤 , 燕明晓 , 马英石 , 等 . 基于八叉树结构的三维体素模型检索 [J ] . 计算机学报 , 2021 , 44 ( 2 ): 334 - 346 .

ZHANG M D , YAN M X , MA Y S , et al . 3D voxel model retrieval based on Octree structure [J ] . Chinese Journal of Computers , 2021 , 44 ( 2 ): 334 - 346 .

杨军 , 王亦民 . 基于深度卷积神经网络的三维模型识别 [J ] . 重庆邮电大学学报(自然科学版) , 2019 , 31 ( 2 ): 253 - 260 .

YANG J , WANG Y M . 3D model recognition based on depth convolution neural network [J ] . Journal of Chongqing University of Posts and Telecommunications (Natural Science Edition) , 2019 , 31 ( 2 ): 253 - 260 .

郑乐乐 . 基于凹凸性和形状直径函数的三维模型分割 [D ] . 太原:中北大学 , 2018 .

ZHENG L L . Three-dimensional model segmentation based on weak convexity and shape diameter function [D ] . Taiyuan:North University of China , 2018 .

CHAKRABORTY S , PAUL D , DAS S , et al . Automated clustering of high-dimensional data with a feature weighted mean shift algorithm [C ] // Proceedings of the 35th AAAI Conference on Artificial Intelligence/33rd Conference on Innovative Applications of Artificial Intelligence/11th Symposium on Educational Advances in Artificial Intelligence,Electr Network , 2021 .

LIU J , LI R , LIU Y , et al . Research on signal-to-noise ratio estimation algorithm in wireless communication [J ] . Computer Engineering and Application , 2020 , 56 ( 18 ): 82 - 9 .

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