3D Watermarking Research Articles

Three-dimensional optical watermarking scheme using compressed sensing in integral imaging system

The elemental image array (EIA) is a special form of the integral imaging three-dimensional (3D) display system for recording, transmitting and displaying 3D image information, which consists of a series of small image units taken from different perspectives. There is an urgent need for protecting the copyright of EIA to improve security and anti-aggressive capability. In this paper, we propose a 3D optical watermarking scheme for integral imaging system based on compressed sensing (CS) theory. The proposed watermarking scheme consists of two subsystems, one is the EIA watermark compression and embedding subsystem, and the other is the EIA watermark extraction and display subsystem. CS theory using by phase coding mask is applied for realizing the EIA encryption and compression simultaneously, which can reduce the total amount of embedded watermark information, expand the space of secret keys and make the system more flexible and compact. The experimental results are presented to demonstrate the feasibility and effectiveness of the proposed method. The parameters of the integral imaging watermark encryption system, including the focal length and aperture of the lenslet array, the object distance, the wavelength, the diffraction distance, and the measurement matrix of CS, can all be used as the secret keys. The method proposed in this paper can effectively broaden the keys space and enhance the security of the integral image 3D display system.

3D Video watermarking for MVD based view-synthesis and RST attack

3D Video watermarking for MVD based view-synthesis and RST attack

3D Object Watermarking from Data Hiding in the Homomorphic Encrypted Domain

For over a decade, 3D objects are an increasingly popular form of media. It has become necessary and urgent to secure them during their transmission or archiving. In this article, we propose a new method to obtain a watermarked 3D object from high-capacity data hiding in the encrypted domain. Based on the homomorphic properties of the Paillier cryptosystem, our proposed method allows us to embed several secret messages in the encrypted domain with a high-capacity. These messages can be extracted in the plain-text domain after the 3D object decryption. To the best of our knowledge, we are the first to propose a data hiding method in the encrypted domain where the high-capacity watermark is conserved in the plain-text domain after the 3D object is decrypted. The encryption and the data hiding in the encrypted domain are format compliant and without size expansion, despite the use of the Paillier cryptosystem. Each time a new message is embedded in the encrypted domain, flags are added in order to indicate which blocks are still available for the embedding of additional messages. After the decryption of a watermarked encrypted 3D object, our method produces a watermarked 3D object which is visually very similar to the original 3D object. From the decrypted watermarked 3D object, we can then extract all the embedded messages directly in the plain-text domain, without the need for an auxiliary file. Moreover, large keys are used, rending our method secure for real-life applications.

Exhaustive study on post effect processing of 3D image based on nonlinear digital watermarking algorithm

Abstract In this work, an exhaustive study on post effect processing of three-dimensional (3D) image is carried to solve the problem of nonlinear digital watermarking algorithm. First, through the feature space decomposition method of the host image, the embedded watermark is constructed with the full row or column rank of the matrix, and then the public key is constructed by using the existence of the unitary matrix of the full row rank and column rank matrix, so that the algorithm can embed and extract the watermark in an asymmetric way. Watermark extraction correlation coefficient (ρ) value is 1. When the deformation amplitude of the model is slight and the noise intensity is σ = 0.0001, the watermark can be extracted successfully, and the watermark extraction correlation coefficient (ρ) is 0.92. In addition, the security of the algorithm is analyzed from many angles, the theoretical analysis is given, and verified by the experimental results. The proposed 3D watermarking methods are used to examine the information capacity of various 3D meshes. The 3D watermarking methods’ resistance to noise perturbation and object cropping is also investigated.

A bilateral attention based generative adversarial network for DIBR 3D image watermarking

This paper presents a bilateral attention based generative adversarial network (BAGAN) for depth-image-based rendering (DIBR) 3D image watermarking to protect the image copyright. Convolutional block operations are employed to extract main image features for robust watermarking, but embedding watermark into some features will degrade image quality much. To relieve this kind of image distortion, the bilateral attention module (BAM) is utilized by mining correlations of the center view and the depth map to compute attention of the 3D image for guiding watermark to distribute over different image regions. Since a modality gap exists between the center view and the depth map, a cross-modal feature fusion module (CMFFM) is designed for BAM to bridge the cross-view gap. Because the depth map has lots of flat background information including many redundant features, to prune them, the depth redundancy elimination module (DREM) is used for cross-view feature fusion. In the decoder, two extractors with the same structure are built to recover watermark from the center view and the synthesized view, respectively. In addition, the discriminator is supposed to build a competitive relationship with the encoder to increase the image quality. The noise sub-network is used to train different image attacks for robustness. Extensive experimental results have demonstrated that the proposed BAGAN can obtain higher watermarking invisibility and robustness compared with existing DIBR 3D watermarking methods. Ablation experiments have also proven the effectiveness of DREM, CMFFM and BAM on BAGAN.

Efficient secure optical DWT-based watermarked 3D video transmission over MC-CDMA wireless channel

Efficient secure optical DWT-based watermarked 3D video transmission over MC-CDMA wireless channel

Deep 3D mesh watermarking with self-adaptive robustness

Robust 3D mesh watermarking is a traditional research topic in computer graphics, which provides an efficient solution to the copyright protection for 3D meshes. Traditionally, researchers need manually design watermarking algorithms to achieve sufficient robustness for the actual application scenarios. In this paper, we propose the first deep learning-based 3D mesh watermarking network, which can provide a more general framework for this problem. In detail, we propose an end-to-end network, consisting of a watermark embedding sub-network, a watermark extracting sub-network and attack layers. We employ the topology-agnostic graph convolutional network (GCN) as the basic convolution operation, therefore our network is not limited by registered meshes (which share a fixed topology). For the specific application scenario, we can integrate the corresponding attack layers to guarantee adaptive robustness against possible attacks. To ensure the visual quality of watermarked 3D meshes, we design the curvature consistency loss function to constrain the local geometry smoothness of watermarked meshes. Experimental results show that the proposed method can achieve more universal robustness while guaranteeing comparable visual quality.

A robust scheme for copy detection of 3D object point clouds

Most existing 3D geometry copy detection research focused on 3D watermarking, which first embeds “watermarks” and then detects the added watermarks. However, this kind of methods is non-straightforward and may be less robust to attacks such as cropping and noise. In this paper, we focus on a fundamental and practical research problem: judging whether a point cloud is plagiarized or copied to another point cloud in the presence of several manipulations (e.g., similarity transformation, smoothing). We propose a novel method to address this critical problem. Our key idea is first to align the two point clouds and then calculate their similarity distance. We design three different measures to compute the similarity. We also introduce two strategies to speed up our method. Comprehensive experiments and comparisons demonstrate the effectiveness and robustness of our method in estimating the similarity of two given 3D point clouds.

Embedding Information into or onto Additively Manufactured Parts: A Review of QR Codes, Steganography and Watermarking Methods.

The paper gives a detailed review of the approaches adopted for embedding information into/onto additively manufactured parts. The primary purpose of this paper is to review all the techniques adopted for embedding information, highlight notable trends and improvements in these works, and provide design and manufacturing pipelines to realize most of these works. It classifies these approaches into four different categories and summarizes the works carried out in each field. It also compares all the results in textual and tabular forms and then gives a detailed conclusion of the best works in terms of application and effectiveness. The four categories discussed are 3D QR codes, 3D watermarking, steganography and nonclassified methods. Lastly, it discusses the future extensions and potential improvements in the field of embedding information, while exploring manufacturing technologies.

A Robust 3-D Medical Watermarking Based on Wavelet Transform for Data Protection

In a telemedicine diagnosis system, the emergence of 3D imaging enables doctors to make clearer judgments, and its accuracy also directly affects doctors’ diagnosis of the disease. In order to ensure the safe transmission and storage of medical data, a 3D medical watermarking algorithm based on wavelet transform is proposed in this paper. The proposed algorithm employs the principal component analysis (PCA) transform to reduce the data dimension, which can minimize the error between the extracted components and the original data in the mean square sense. Especially, this algorithm helps to create a bacterial foraging model based on particle swarm optimization (BF-PSO), by which the optimal wavelet coefficient is found for embedding and is used as the absolute feature of watermark embedding, thereby achieving the optimal balance between embedding capacity and imperceptibility. A series of experimental results from MATLAB software based on the standard MRI brain volume dataset demonstrate that the proposed algorithm has strong robustness and make the 3D model have small deformation after embedding the watermark.

High Efficiency Crypto-Watermarking System Based on Clifford-Multiwavelet for 3D Meshes Security

Since 3D mesh security has become intellectual property, 3D watermarking algorithms have continued to appear to secure 3D meshes shared by remote users and saved in distant multimedia databases. The novelty of our approach is that it uses a new Clifford-multiwavelet transform to insert copyright data in a multiresolution domain, allowing us to greatly expand the size of the watermark. After that, our method does two rounds of insertion, each applying a different type of Clifford-wavelet transform. Before being placed into the Clifford-multiwavelet coefficients, the watermark, which is a mixture of the mesh description, source mesh signature (produced using SHA512), and a logo encrypted using the RSA (Ronald Shamir Adleman) technique, is encoded using Turbo-code. Using the Least Significant Bit method steps, data embedding involves modulation and insertion processes. Finally, the watermarked mesh is reconstructed using the inverse Clifford-multiwavelet transform. Due to the utilization of a hybrid insertion domain, our technique has demonstrated a very high insertion rate while retaining mesh quality. The mesh is watermarked, and the extracted data is acquired in real-time. Our approach is also resistant to the most common types of attacks. Our findings reveal that the current approach improves on previous efforts.

Research on watermark printing technology of STL model based on Menger curvature

In order to solve the data protection problem of STL model, this paper proposes a 3D printing watermarking method based on Menger curvature and K-means clustering algorithm. By comparing the research contents of 3D mesh model watermarking algorithm and two 3D printing watermarking methods, the 3D printing watermarking method is applied based on Menger curvature and K-means clustering algorithm. The method flow, watermark embedding and watermark extraction are discussed. Finally, the experimental results show that this method can not only improve the invisibility of model watermark, but also be robust to geometric attacks such as rotation, scaling and translation.

ThermoTag: A Hidden ID of 3D Printers for Fingerprinting and Watermarking

To address the increasing challenges of counterfeit detection and IP protection for 3D printing, we propose that every 3D printer holds unique fingerprinting features characterized by the thermodynamic properties of the extruder hot-end and can be used as a new way of 3D watermarking. We prove that these physical fingerprints resulting from manufacturing imperfections and system variations exhibit distinct heating responses, namely “ThermoTag,” which can be represented as the distinguishable thermodynamic processes and, ultimately, the temperature readings during the preheating process. Experimental results show that, by only changing the hot-ends of the same model on the same 3D printer, we can achieve about 92% identification accuracy amongst 45 hot-ends. The permanence and robustness of ThermoTag for the same hot-end were examined, throughout a period of one month with hundreds of trials under different environmental temperature settings. Leveraging the hidden ThermoTag, an example of watermarking scheme in 3D printing is presented and evaluated.

Rapid and Blind Watermarking Approach of the 3D Objects Using QR Code Images for Securing Copyright.

Watermarking techniques in a wide range of digital media was utilized as a host cover to hide or embed a piece of information message in such a way that it is invisible to a human observer. This study aims to develop an enhanced rapid and blind method for producing a watermarked 3D object using QR code images with high imperceptibility and transparency. The proposed method is based on the spatial domain, and it starts with converting the 3D object triangles from the three-dimensional Cartesian coordinate system to the two-dimensional coordinates domain using the corresponding transformation matrix. Then, it applies a direct modification on the third vertex point of each triangle. Each triangle's coordinates in the 3D object can be used to embed one pixel from the QR code image. In the extraction process, the QR code pixels can be successfully extracted without the need for the original image. The imperceptibly and the transparency performances of the proposed watermarking algorithm were evaluated using Euclidean distance, Manhattan distance, cosine distance, and the correlation distance values. The proposed method was tested under various filtering attacks, such as rotation, scaling, and translation. The proposed watermarking method improved the robustness and visibility of extracting the QR code image. The results reveal that the proposed watermarking method yields watermarked 3D objects with excellent execution time, imperceptibility, and robustness to common filtering attacks.

Steganalysis of meshes based on 3D wavelet multiresolution analysis

3D steganalysis aims to find the information hidden in 3D models and graphical objects. It is assumed that the information was hidden by 3D steganography or watermarking algorithms. A new set of 3D steganalysis features, derived by using multiresolution 3D wavelet analysis, is proposed in this research study. 3D wavelets relate a given mesh representation with its lower and higher graph resolutions by means of a set of Wavelet Coefficient Vectors (WCVs). The 3D steganalysis features are derived from transformations between a given mesh and its corresponding higher and lower resolutions. They correspond to geometric measures such as ratios and angles between various geometric measures. These features are shown to significantly increase the steganalysis accuracy when detecting watermarks which have been embedded by 3D wavelet-based watermarking algorithms. The proposed features, when used in combination with a previously proposed feature set, is shown to provide the best results in detecting the hidden information embedded by other information hiding algorithms.

3D Printing Watermarking Algorithm Based on 2D Slice Mean Distance

3D Printing Watermarking Algorithm Based on 2D Slice Mean Distance

A vector-based watermarking scheme for 3D models using block rearrangements

Watermarking schemes help to secure the ownership, authenticity, and copyright-related security issues of electronic data. Digital watermarking is used to enhance the copyright protection of the 3D models thus overcoming the integrity violations. An efficient, robust, semi-blind computationally secure DWT-based watermarking is proposed for 3D models. Firstly, a block segmentation of the vertices is performed on the horizontally or vertically scrambled host 3D model. The secret watermark is embedded into the lower frequency band of each segment using Discrete Wavelet Transform (DWT). The proposed scheme employs block rearrangement to scramble the host 3D model so as to enhance the security and fidelity of the embedded watermark. Reverse scrambling and inverse DWT is accomplished for constructing the watermarked model. Semi-blind extraction process achieved a successful retrieval of the secret watermark from the watermarked 3D model. A simulation study with a variety of 3D models evidenced the performance of the proposed watermarking scheme in terms of geometrical attacks, robustness and degradation affect.

A vector-based watermarking scheme for 3D models using block rearrangements

Watermarking schemes help to secure the ownership, authenticity, and copyright-related security issues of electronic data. Digital watermarking is used to enhance the copyright protection of the 3D models thus overcoming the integrity violations. An efficient, robust, semi-blind computationally secure DWT-based watermarking is proposed for 3D models. Firstly, a block segmentation of the vertices is performed on the horizontally or vertically scrambled host 3D model. The secret watermark is embedded into the lower frequency band of each segment using Discrete Wavelet Transform (DWT). The proposed scheme employs block rearrangement to scramble the host 3D model so as to enhance the security and fidelity of the embedded watermark. Reverse scrambling and inverse DWT is accomplished for constructing the watermarked model. Semi-blind extraction process achieved a successful retrieval of the secret watermark from the watermarked 3D model. A simulation study with a variety of 3D models evidenced the performance of the proposed watermarking scheme in terms of geometrical attacks, robustness and degradation affect.

Watermarking in 3D Models Using Depth Path

This paper presents a 3D watermarking model based on the nearest distance between two vertices in mesh, where the embedding path moves as deep as possible until the embedding data is completed. The proposed algorithm achieved good results according to invisibility and robustness. The visibility was measured in termof Root Mean Square Error (RMSE) and Hausdroff Distance (HD), which obtained good results. As related to robustness, the proposed method showed resistance to geometrical attack (translation, scaling and rotation) as well as acceptable resistance to signal processing attacks like noise addition and simplification.

Hypothesis-based vertex shift method for embedding secret logos in thegeometric features of 3D objects

A recent challenge in information technology is to protect secret data and preserve the ownership of a product. There are many duplicate products being released on a daily basis. Owners have a high risk in proving their products. Watermarking is a technique used to preserve ownership by hiding the owner's information in their products. The proposed hypothesis-based vertex shifting algorithm embeds 2D secret logos in 3D cover objects. The 3D objects are represented using vertices and facets. 3D watermarking faces various challenges and one among them is capacity. In this work, capacity is addressed by using a hypothesis-based vertex shift method that enables the embedding process for all the coordinates of the vertex. The method works by partitioning the vertex based on a shift factor called svalue. The svalue is chosen based on the visual quality of the watermarked object. The metrics used for testing are bit error rate for the recovered watermark, peak-to-signal noise ratio, and vertex signal-to-noise ratio (VSNR) of the watermarked 3D image. The proposed algorithm shows that a maximum of 3 bits can be embedded in a vertex when compared with the existing algorithms. The VSNR value of the proposed algorithm is high (125.87) compared to the existing algorithms. This shows that the algorithm withstands visual quality inspection. Hence, it is a robust watermarking algorithm for embedding secret logos into 3D objects with better visual quality and higher resilience against translation and uniform scaling attacks.