Steganography for three-dimensional models

We present a data hiding algorithm for 3D models. It is based on a substitutive procedure in the spatial domain. We propose a Virtual Multi-Level Embed Procedure to embed information based on shifting the message point by its virtual geometrical property, the order of which is assigned by principal component analysis. We have defined and validated an effective metric of distortion anticipation, which can help us easily anticipate and control the distortion rate. Experimental results show that the proposed technique is efficient and secure, has high capacity and low distortion, and is robust against affine transformations. It provides a reversible method and has proven to be feasible in data hiding

A Study of Low Distortion Sampling Techniques and Distortion Free Data Hiding Algorithms

Photorealistic Rendering (PR) is an active research topic in the computer graphics community. It aims to produce an image of the highest quality that is indistinguishable to a real scene. By utilizing a physical based equation, the rendering equation, we can describe a virtual scene with physical character, and then we can render the realistic image by computer operation. In order to calculate the rendering equation, the Monte Carlo method is most often used. The sampling technique is the actual operating technique of the Monte Carlo method. In the sampling technique, the variance represents the potency of the whole operation. Usually, high variance means low efficiency. Compared to the basic sampling technique and the uniform sampling technique, the stratified sampling technique is an effective sampling technique with lower variance. This low distortion sampling technique is an advanced technique based on the stratified sampling technique in order to enhance the potency further. In contrast, in the PR topic, the basic technique samples random samples on the light source. For a different light source, the corresponding sampling technique is different. There are corresponding sampling techniques for familiar geometries, such as rectangle, triangle, disc, cylinder cone, ellipse, and torus. In the first part of this paper, we propose a low distortion sampling technique for an ellipse. By the low distortion mapping relation, we calculate the corresponding sampling function. Our technique provides ellipse sampling with efficiency, stratified sampling, and low distortion. On the other hand, in current steganographic techniques, the secret message is hidden in the value domain of the cover medium. When we hide the message into the cover medium and get the stego medium, there are always distortions between the cover and the stego medium. In existing researches, the goals usually are to reduce distortion or to enhance the capacity under the given distortions. Unlike traditional steganography, distortion free steganography hides the message in the structure domain of the medium. In that way, when we use the standard viewer to open those two files, we can deduce that there is no distortion between the cover and the stego medium,. Since the message is hidden in the structure domain of the media, for different media the corresponding distortion free steganographic techniques are different. The most common distortion for steganography is the permutation scheme, which works on those data structures with the condition that the order of the element is independent to the final result, such as the 3D polygonal mesh file. In the second part of this paper, we propose two distortion free steganographic techniques. The first technique belongs to the permutation scheme. Our technique is an advance technique of Bogomjakov et al's algorithm. By changing the encoding part, our technique achieves higher capacity in the same condition. The second distortion free steganographic technique is based on the Radiance RGBE file, which is a commonly used high dynamic range image. As we say, the message is hidden in the structure domain. Our technique is based on the adaptive run-length encoding, which is used in the Radiance RGBE file. By changing the encoding process of the ARLE, we can achieve the goal of distortion free steganography.致謝 i 摘要 ii Abstract v List of Figures ix List of Tables xi Chapter 1 Introduction 1 1.1 Overview of Sampling Techniques 3 1.2 Overview of Distortion Free Steganography 5 1.3 Thesis Organization 7 Chapter 2 Background and Related Works 8 2.1 Monte Carlo Methods 8 2.2 Sampling Techniques 9 2.2.1 Uniform Sampling Techniques 10 2.2.2 Stratified Sampling Techniques 12 2.2.3 Low Distortion Sampling Techniques 14 2.3 Distortion Free Steganography 16 2.3.1 Standard Permutation Steganography 17 2.3.2 Bogomjakov et al.’s Algorithm 18 2.3.3 High Dynamic Range Image Steganography 20 2.3.4 Radiance RGBE file 21 Chapter 3 A Low Distortion Sampling Technique for an Ellipse 23 3.1 Uniform Sampling Function for an Ellipse 23 3.2 Low Distortion Sampling Function 25 3.3 An Application for Photorealistic Rendering 28 3.4 Experimental Results 29 3.5 Summary 34 Chapter 4 Distortion Free Steganography for Three-Dimensional Models 35 4.1 The Proposed Algorithm 35 4.1.1 The Encoding Process 37 4.1.2 The Decoding Process 40 4.2 An Analysis of the Expected Capacity 43 4.3 Experimental Results and Analysis 44 4.4 Summary 51 Chapter 5 Distortion Free Steganography for High Dynamic Range Images 52 5.1 The General ARLE Scheme 53 5.1.1 The Hiding Process 54 5.1.2 The Extracting Process 56 5.1.3 The Loss of Compression Ratio 57 5.2 The Specific ARLE Scheme 58 5.2.1 Transfer Functions between the Binary Data and the Index 59 5.2.2 The Embedding Process 61 5.2.3 The Extracting Process 63 5.3 The Experimental Results 65 5.3.1 Experimental Results of the General ARLE Scheme 68 5.3.2 Experiment Results of the Specific ARLE Scheme 69 5.4 Summary 70 Chapter 6 Conclusions and Future Work 71 References 74 Index 8