A Distortion-Free Data Hiding Scheme for Triangular Meshes Based on Recursive Subdivision

Tsai, Yuan‐Yu

doi:10.1155/2016/4267419

Cited by 14 publications

(3 citation statements)

References 13 publications

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“…The blind extraction algorithm has high embedding capacity and less distortion. Tsai [47] proposed steganography scheme in 3D image mesh models by modifying the topology of the cover model, using recursive triangle subdivision process. The proposed approach has been shown to be robust against the vertex reordering attack but is not able to withstand the intentional attacks on the stego model.…”

Section: Topological Domain Based Steganographymentioning

confidence: 99%

Comprehensive survey of 3D image steganography techniques

Girdhar

Kumar

2018

IET Image Processing

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Section: Topological Domain Based Steganographymentioning

confidence: 99%

Comprehensive survey of 3D image steganography techniques

Girdhar

Kumar

2018

IET Image Processing

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“…This unfortunately allows for a limited embedding capacity when compared to other spatial domain schemes. Tsai [28] proposed a blind reversible topological steganography scheme using recursive triangle subdivision which was proven to withstand af ine translation. However, blind extraction fails when the stego object is subject to noise.…”

Section: Introductionmentioning

confidence: 99%

A robust high capacity Gray code-based double layer security scheme for secure data embedding in 3D objects

Mostafa¹,

Alexan²

2022

ITU J-FET

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In this study, we propose a novel high capacity double layer algorithm for secure data embedding in 3D objects. This is achieved by aggregating a cryptography layer through the deployment of Blowfish or AES-128 algorithms to a steganography layer based on a Gray code sequence that individuates the order of the vertices over which the embedding will occur. Thereafter, the 3D objects are preprocessed and the secret data is embedded over the vertices' x-, y- and z- coordinates. Hence, the 3D object capacity is effectively utilized. The secret data is then blindly extracted from the stego 3D object. The performance of the proposed algorithm is extensively investigated and compared to other commensurate studies from the literature. The proposed algorithm withstands vertex reordering and common geometrical similarity attacks such as reflection, uniform scaling, rotation and translation. Additionally, it partially withstands smoothing. The achieved numerical results demonstrate the superiority of the proposed algorithm in terms of capacity, computational complexity, imperceptibility, distortion and robustness.

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“…According to literature, existing RDH methods of 3D models are mainly divided into four domains: spatial domain, transform domain, compressed domain and encrypted domain. [23][24][25][26][27][28][29][30] embedded additional data into 3D models by slightly modifying vertex coordinates. Transform domain RDH methods [31,32] embedded additional data into the transformation coefficients of the models.…”

Section: Introductionmentioning

confidence: 99%

Separable Reversible Data Hiding Based on Integer Mapping and MSB Prediction for Encrypted 3D Mesh Models

Xu¹,

Tang²,

Luo³

et al. 2021

Cogn Comput

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Reversible data hiding in encrypted domain (RDH-ED) has received tremendous attention from the research community because data can be embedded into cover media without exposing it to the third party data hider and the cover media can be losslessly recovered after the extraction of the embedded data. Although, in recent years, extensive studies have been carried out about images based RDH-ED, little attention is paid to RDH-ED in 3D mesh models due to its complex data structure and irregular geometry. We propose a separable RDH-ED method for 3D mesh models based on MSB (most significant bit) prediction. Firstly, we divide all the vertices of the mesh into the "embedded" set and "reference" set according to topological information between vertices, and calculate the MSB prediction errors for the vertices of the "embedded" set. Then, bit-stream encryption is used to encrypt the mesh. Finally, data is embedded by replacing the MSB of the encrypted vertex coordinates of the "embedded" set by the additional data bits. Recipient with data hiding key can correctly extract the additional data from the marked encrypted mesh. Recipient with encryption key can recover the mesh perfectly by using MSB prediction. Experimental results show that the proposed method has higher embedding capacity and higher quality of the recovered meshes compared to the existing RDH-ED method for 3D meshes based on symmetric encryption.

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A Distortion-Free Data Hiding Scheme for Triangular Meshes Based on Recursive Subdivision

Cited by 14 publications

References 13 publications

Comprehensive survey of 3D image steganography techniques

Comprehensive survey of 3D image steganography techniques

A robust high capacity Gray code-based double layer security scheme for secure data embedding in 3D objects

Separable Reversible Data Hiding Based on Integer Mapping and MSB Prediction for Encrypted 3D Mesh Models

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