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

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

Steganalytic Methods for 3D Objects

This PhD thesis provides new research results in the area of using 3D features for steganalysis. The research study presented in the thesis proposes new sets of 3D features, greatly extending the previously proposed features. The proposed steganlytic feature set includes features representing the vertex normal, curvature ratio, Gaussian curvature, the edge and vertex position of the 3D objects in the spherical coordinate system. Through a second contribution, this thesis presents a 3D wavelet multiresolution analysis-based steganalytic method. The proposed method extracts the 3D steganalytic features from meshes of different resolutions. The third contribution proposes a robustness and relevance-based feature selection method for solving the cover-source mismatch problem in 3D steganalysis. This method selects those 3D features that are robust to the variation of the cover source, while preserving the relevance of such features to the class label. All the proposed methods are applied for identifying stego-meshes produced by several steganographic algorithms

Robust feature-based 3D mesh segmentation and visual mask with application to QIM 3D watermarking

The last decade has seen the emergence of 3D meshes in industrial, medical and entertainment applications. Many researches, from both the academic and the industrial sectors, have become aware of their intellectual property protection arising with their increasing use. The context of this master thesis is related to the digital rights management (DRM) issues and more particularly to 3D digital watermarking which is a technical tool that by means of hiding secret information can offer copyright protection, content authentication, content tracking (fingerprinting), steganography (secret communication inside another media), content enrichment etc. Up to now, 3D watermarking non-blind schemes have reached good levels in terms of robustness against a large set of attacks which 3D models can undergo (such as noise addition, decimation, reordering, remeshing, etc.). Unfortunately, so far blind 3D watermarking schemes do not present a good resistance to de-synchronization attacks (such as cropping or resampling). This work focuses on improving the Spread Transform Dither Modulation (STDM) application on 3D watermarking, which is an extension of the Quantization Index Modulation (QIM), through both the use of the perceptual model presented, which presents good robustness against noising and smoothing attacks, and the the application of an algorithm which provides robustness noising and smoothing attacks, and the the application of an algorithm which provides robustness against reordering and cropping attacks based on robust feature detection. Similar to other watermarking techniques, imperceptibility constraint is very important for 3D objects watermarking. For this reason, this thesis also explores the perception of the distortions related to the watermark embed process as well as to the alterations produced by the attacks that a mesh can undergo

Watermarked 3D Object Quality Assessment

This work concerns the developing of new perceptual metrics for 3D watermarking quality assessment. Any water- marking algorithm, to be effective, requires that the distortions is inevitably introduces into the watermarked media is imperceptible. This requirements is particularly severe for watermarking of 3D objects where the visual quality of the original model has to be preserved, i.e. the visual aspect of the watermarked object have to be the same of the original one. Several methods based on the knowledge of Human Visual System (HVS) have been developed to achieve this goal for still images and video watermarking. Since now, no similar techniques for watermarking of 3D objects exist. Here, we propose a novel experimental methodology for subjective evaluations of 3D objects and two perceptual metrics for quality assessment of watermarked 3D objects. Such metrics have been developed combining roughness estimation of model surface with psychophysical data collected by subjective experiments based on the proposed methodology. The performances of the proposed metrics are deeply analyzed

Exploiting Spatio-Temporal Coherence for Video Object Detection in Robotics

This paper proposes a method to enhance video object detection for indoor environments in robotics. Concretely, it exploits knowledge about the camera motion between frames to propagate previously detected objects to successive frames. The proposal is rooted in the concepts of planar homography to propose regions of interest where to find objects, and recursive Bayesian filtering to integrate observations over time. The proposal is evaluated on six virtual, indoor environments, accounting for the detection of nine object classes over a total of ∼ 7k frames. Results show that our proposal improves the recall and the F1-score by a factor of 1.41 and 1.27, respectively, as well as it achieves a significant reduction of the object categorization entropy (58.8%) when compared to a two-stage video object detection method used as baseline, at the cost of small time overheads (120 ms) and precision loss (0.92).</p

Polymeco : uma ferramenta de análise e comparação de malhas poligonais

Mestrado em Engenharia Electrónica e TelecomunicaçõesOs modelos definidos usando malhas poligonais são usados em diversas áreas de aplicação para representar diferentes objectos e estruturas. Dependendo da aplicação, pode ser necessário processar esses modelos, por exemplo, para diminuir a sua complexidade (simplificação). Este processamento introduz diferenças, em relação ao modelo original, cuja avaliação é um passo fundamental para permitir escolher a sequência de operações e os métodos de processamento que permitam a obtenção de melhores resultados. Apesar de algumas ferramentas de análise e comparação das características de malhas poligonais serem descritas na literatura, pouca atenção tem sido prestada à forma como os dados provenientes dessa análise e comparação podem ser visualizados. Para além disso, devem ser disponibilizadas várias funcionalidades de forma a permitir uma utilização sistemática destas ferramentas, assim como uma adequada análise e exploração dos dados fornecidos. O PolyMeCo — uma ferramenta de análise e comparação das características de malhas poligonais — foi projectado e desenvolvido tendo em conta os objectivos acima referidos. Através de um ambiente integrado onde diferentes opções de visualização estão disponíveis e podem ser usadas de forma coordenada, o PolyMeCo permite aos utilizadores uma melhor compreensão dos dados resultantes da aplicação dos números de mérito disponibilizados. Esta nova ferramenta foi usada com sucesso em dois trabalhos de investigação: (1) para comparar as características das malhas resultantes de dois algoritmos de simplificação de malhas poligonais, e (2) para testar a aplicabilidade dos números de mérito que disponibiliza como estimadores da qualidade de modelos poligonais, tal como percebida pelos utilizadores. ABSTRACT: Polygonal meshes are used in several application areas to model different objects and structures. Depending on the application, such models sometimes have to be processed to, for instance, reduce their complexity (mesh simplification). Such processing introduces error, whose evaluation is of paramount importance when choosing the sequence of operations that is to be applied for a particular purpose. Although some mesh analysis and comparison tools are described in the literature, little attention has been given to the way mesh features (analysis) and mesh comparison results can be visualized. Moreover, particular functionalities have to be made available by such tools, to enable systematic use and proper data analysis and exploration. PolyMeCo — a tool for polygonal mesh analysis and comparison — was designed and developed taking the above objectives into account. It enhances the way users perform mesh analysis and comparison, by providing an integrated environment where various mesh quality measures and several visualization options are available and can be used in a coordinated way, thus leading to greater insight into the visualized data. This new tool has been successfully applied in two research works: (1) to compare between mesh simplification algorithms, and (2) to study the applicability of the provided computational measures as estimators of user perceived quality as obtained through an observer study

Out of the archaeologist's desk drawer: communicating archaeological data online

During archaeological field work a huge amount of data is collected, processed and elaborated for further studies and scientific publications. However, access and communication of linked data; associated tools for interrogation, analysis and sharing are often limited at the first stage of the archaeological research, mainly due to issues related to IPR. Information is often released months if not years after the fieldwork. Nowadays great deal of archaeological data is 'born digital' in the field or lab. This means databases, pictures and 3D models of finds and excavation contexts could be available for public communication and sharing. Researchers usually restrict access to their data to a small group of people. It follows that data sharing is not so widespread among archaeologists, and dissemination of research is still mostly based on traditional pre-digital means like scientific papers, journal articles and books. This project has implemented a web approach for sharing and communication purposes, exploiting mainly open source technologies which allow a high level of interactivity. The case study presented is the newly Mithraeum excavated in Ostia Antica archaeological site in the framework of the Ostia Marina Project