Euclidean Distance Distortion Based Robust and Blind Mesh Watermarking

The three-dimensional (3D) polygonal meshes are recently widely used in several domains, which necessitate the realistic visualization of the objects. Moreover, there is an urgent need to protect the 3D data properties for preventing unauthorized reproduction. The 3D digital watermarking technology is one of the best solutions to protect data from piracy during transmission through the internet. The current work proposed a novel robust watermarking scheme of polygonal meshes for copyright protection purposes. The proposed algorithm is based on the characteristics of the mesh geometry to embed a sequence of data bits into the object by slightly adjusting the vertex positions. Furthermore, the proposed method used a blind detection scheme. The watermarked model is perceptually indistinguishable from the original one and the embedded watermark is invariant to affine transformation. Through simulations, the quality of the watermarked object as well as the inserted watermark robustness against various types of attacks were tested and evaluated to prove the validity and the efficiency of our algorithm

Information Analysis for Steganography and Steganalysis in 3D Polygonal Meshes

Information hiding, which embeds a watermark/message over a cover signal, has recently found extensive applications in, for example, copyright protection, content authentication and covert communication. It has been widely considered as an appealing technology to complement conventional cryptographic processes in the field of multimedia security by embedding information into the signal being protected. Generally, information hiding can be classified into two categories: steganography and watermarking. While steganography attempts to embed as much information as possible into a cover signal, watermarking tries to emphasize the robustness of the embedded information at the expense of embedding capacity. In contrast to information hiding, steganalysis aims at detecting whether a given medium has hidden message in it, and, if possible, recover that hidden message. It can be used to measure the security performance of information hiding techniques, meaning a steganalysis resistant steganographic/watermarking method should be imperceptible not only to Human Vision Systems (HVS), but also to intelligent analysis. As yet, 3D information hiding and steganalysis has received relatively less attention compared to image information hiding, despite the proliferation of 3D computer graphics models which are fairly promising information carriers. This thesis focuses on this relatively neglected research area and has the following primary objectives: 1) to investigate the trade-off between embedding capacity and distortion by considering the correlation between spatial and normal/curvature noise in triangle meshes; 2) to design satisfactory 3D steganographic algorithms, taking into account this trade-off; 3) to design robust 3D watermarking algorithms; 4) to propose a steganalysis framework for detecting the existence of the hidden information in 3D models and introduce a universal 3D steganalytic method under this framework. %and demonstrate the performance of the proposed steganalysis by testing it against six well-known 3D steganographic/watermarking methods. The thesis is organized as follows. Chapter 1 describes in detail the background relating to information hiding and steganalysis, as well as the research problems this thesis will be studying. Chapter 2 conducts a survey on the previous information hiding techniques for digital images, 3D models and other medium and also on image steganalysis algorithms. Motivated by the observation that the knowledge of the spatial accuracy of the mesh vertices does not easily translate into information related to the accuracy of other visually important mesh attributes such as normals, Chapters 3 and 4 investigate the impact of modifying vertex coordinates of 3D triangle models on the mesh normals. Chapter 3 presents the results of an empirical investigation, whereas Chapter 4 presents the results of a theoretical study. Based on these results, a high-capacity 3D steganographic algorithm capable of controlling embedding distortion is also presented in Chapter 4. In addition to normal information, several mesh interrogation, processing and rendering algorithms make direct or indirect use of curvature information. Motivated by this, Chapter 5 studies the relation between Discrete Gaussian Curvature (DGC) degradation and vertex coordinate modifications. Chapter 6 proposes a robust watermarking algorithm for 3D polygonal models, based on modifying the histogram of the distances from the model vertices to a point in 3D space. That point is determined by applying Principal Component Analysis (PCA) to the cover model. The use of PCA makes the watermarking method robust against common 3D operations, such as rotation, translation and vertex reordering. In addition, Chapter 6 develops a 3D specific steganalytic algorithm to detect the existence of the hidden messages embedded by one well-known watermarking method. By contrast, the focus of Chapter 7 will be on developing a 3D watermarking algorithm that is resistant to mesh editing or deformation attacks that change the global shape of the mesh. By adopting a framework which has been successfully developed for image steganalysis, Chapter 8 designs a 3D steganalysis method to detect the existence of messages hidden in 3D models with existing steganographic and watermarking algorithms. The efficiency of this steganalytic algorithm has been evaluated on five state-of-the-art 3D watermarking/steganographic methods. Moreover, being a universal steganalytic algorithm can be used as a benchmark for measuring the anti-steganalysis performance of other existing and most importantly future watermarking/steganographic algorithms. Chapter 9 concludes this thesis and also suggests some potential directions for future work

Steganalysis of 3D objects using statistics of local feature sets

3D steganalysis aims to identify subtle invisible changes produced in graphical objects through digital watermarking or steganography. Sets of statistical representations of 3D features, extracted from both cover and stego 3D mesh objects, are used as inputs into machine learning classifiers in order to decide whether any information was hidden in the given graphical object. The features proposed in this paper include those representing the local object curvature, vertex normals, the local geometry representation in the spherical coordinate system. The effectiveness of these features is tested in various combinations with other features used for 3D steganalysis. The relevance of each feature for 3D steganalysis is assessed using the Pearson correlation coefficient. Six different 3D watermarking and steganographic methods are used for creating the stego-objects used in the evaluation study

3D Mesh Steganalysis using local shape features

Steganalysis aims to identify those changes performed in a specific media with the intention to hide information. In this paper we assess the efficiency, in finding hidden information, of several local feature detectors. In the proposed 3D ste- ganalysis approach we first smooth the cover object and its corresponding stego-object obtained after embedding a given message. We use various operators in order to extract lo- cal features from both the cover and stego-objects, and their smoothed versions. Machine learning algorithms are then used for learning to discriminate between those 3D objects which are used as carriers of hidden information and those are not used. The proposed 3D steganalysis methodology is shown to provide superior performance to other approaches in a well known database of 3D objects

Robust digital watermarking for compressed 3D models based on polygonal representation

Multimedia has recently played an increasingly important role in various domains, including Web applications, movies, video game and medical visualization. The rapid growth of digital media data over the Internet, on the other hand, makes it easy for anyone to access, copy, edit and distribute digital contents such as electronic documents, images, sounds and videos. Motivated by this, much research work has been dedicated to develop methods for digital data copyright protection, tracing the ownership, and preventing illegal duplication or tampering. This paper introduces a methodology of robust digital watermarking based on a well-known spherical wavelet transformation, applied to 3D compressed model based on polygonal representation using a neural network. It will be demonstrated in this work that applying a watermarking algorithm on a compressed domain of a 3D object is more effective, efficient, and robust than when applied on a normal domain

Copyright Protection of 3D Digitized Artistic Sculptures by Adding Unique Local Inconspicuous Errors by Sculptors

In recent years, digitization of cultural heritage objects, for the purpose of creating virtual museums, is becoming increasingly popular. Moreover, cultural institutions use modern digitization methods to create three-dimensional (3D) models of objects of historical significance to form digital libraries and archives. This research aims to suggest a method for protecting these 3D models from abuse while making them available on the Internet. The proposed method was applied to a sculpture, an object of cultural heritage. It is based on the digitization of the sculpture altered by adding local clay details proposed by the sculptor and on sharing on the Internet a 3D model obtained by digitizing the sculpture with a built-in error. The clay details embedded in the sculpture are asymmetrical and discreet to be unnoticeable to an average observer. The original sculpture was also digitized and its 3D model created. The obtained 3D models were compared and the geometry deviation was measured to determine that the embedded error was invisible to an average observer and that the watermark can be extracted. The proposed method simultaneously protects the digitized image of the artwork while preserving its visual experience. Other methods cannot guarantee this

Copyright Protection of 3D Digitized Artistic Sculptures by Adding Unique Local Inconspicuous Errors by Sculptors

In recent years, digitization of cultural heritage objects, for the purpose of creating virtual museums, is becoming increasingly popular. Moreover, cultural institutions use modern digitization methods to create three-dimensional (3D) models of objects of historical significance to form digital libraries and archives. This research aims to suggest a method for protecting these 3D models from abuse while making them available on the Internet. The proposed method was applied to a sculpture, an object of cultural heritage. It is based on the digitization of the sculpture altered by adding local clay details proposed by the sculptor and on sharing on the Internet a 3D model obtained by digitizing the sculpture with a built-in error. The clay details embedded in the sculpture are asymmetrical and discreet to be unnoticeable to an average observer. The original sculpture was also digitized and its 3D model created. The obtained 3D models were compared and the geometry deviation was measured to determine that the embedded error was invisible to an average observer and that the watermark can be extracted. The proposed method simultaneously protects the digitized image of the artwork while preserving its visual experience. Other methods cannot guarantee this

Copyright Protection of 3D Digitized Sculptures by Use of Haptic Device for Adding Local-Imperceptible Bumps

This research aims to improve some approaches for protecting digitized 3D models of cultural heritage objects such as the approach shown in the authors\u27 previous research on this topic. This technique can be used to protect works of art such as 3D models of sculptures, pottery, and 3D digital characters for animated film and gaming. It can also be used to preserve architectural heritage. In the research presented here adding protection to the scanned 3D model of the original sculpture was achieved using the digital sculpting technique with a haptic device. The original 3D model and the model with added protection were after that printed at the 3D printer, and then such 3D printed models were scanned. In order to measure the thickness of added protection, the original 3D model and the model with added protection were compared. Also, two scanned models of the printed sculptures were compared to define the amount of added material. The thickness of the added protection is up to 2 mm, whereas the highest difference detected between a matching scan of the original sculpture (or protected 3D model) and a scan of its printed version (or scan of the protected printed version) is about 1 mm

DIGITAL WATERMARKING OF 3D MEDICAL VISUAL OBJECTS

At present, medical equipment provides often 3D models of scanning organs instead of ordinary 2D images. This concept is supported by Digital Imaging and COmmunications in Medicine (DICOM) standard available for telemedicine. This means that the confidential information under transmission ought to be protected by special techniques, particularly digital watermarking scheme instead of textual informative files represented, for example, on CD disks. We propose a multilevel protection, for which a fragile watermark is the first level of protection. The Region Of Interest (ROI) watermark and textual watermarks with information about patient and study (the last ones can be combines as a single textual watermark) form the second level of protection. Encryption of the ROI and textual watermarks using Arnold’s transform is the third level of protection. In the case of 3D models, we find the ROI in each of 2D sliced images, apply the digital wavelet transform or digital shearlet transform (depending on the volume of watermarks) for the ROI and textual watermarks embedding, and embed a fragile watermark using digital Hadamard transform. The main task is to find the relevant regions for embedding. To this and, we develop the original algorithm for selecting relevant regions. The obtained results confirm the robustness of our approach for rotation, scaling, translation, and JPEG attacks