Data Hiding in Digital Video

With the rapid development of digital multimedia technologies, an old method which is called steganography has been sought to be a solution for data hiding applications such as digital watermarking and covert communication. Steganography is the art of secret communication using a cover signal, e.g., video, audio, image etc., whereas the counter-technique, detecting the existence of such as a channel through a statistically trained classifier, is called steganalysis. The state-of-the art data hiding algorithms utilize features; such as Discrete Cosine Transform (DCT) coefficients, pixel values, motion vectors etc., of the cover signal to convey the message to the receiver side. The goal of embedding algorithm is to maximize the number of bits sent to the decoder side (embedding capacity) with maximum robustness against attacks while keeping the perceptual and statistical distortions (security) low. Data Hiding schemes are characterized by these three conflicting requirements: security against steganalysis, robustness against channel associated and/or intentional distortions, and the capacity in terms of the embedded payload. Depending upon the application it is the designer\u27s task to find an optimum solution amongst them. The goal of this thesis is to develop a novel data hiding scheme to establish a covert channel satisfying statistical and perceptual invisibility with moderate rate capacity and robustness to combat steganalysis based detection. The idea behind the proposed method is the alteration of Video Object (VO) trajectory coordinates to convey the message to the receiver side by perturbing the centroid coordinates of the VO. Firstly, the VO is selected by the user and tracked through the frames by using a simple region based search strategy and morphological operations. After the trajectory coordinates are obtained, the perturbation of the coordinates implemented through the usage of a non-linear embedding function, such as a polar quantizer where both the magnitude and phase of the motion is used. However, the perturbations made to the motion magnitude and phase were kept small to preserve the semantic meaning of the object motion trajectory. The proposed method is well suited to the video sequences in which VOs have smooth motion trajectories. Examples of these types could be found in sports videos in which the ball is the focus of attention and exhibits various motion types, e.g., rolling on the ground, flying in the air, being possessed by a player, etc. Different sports video sequences have been tested by using the proposed method. Through the experimental results, it is shown that the proposed method achieved the goal of both statistical and perceptual invisibility with moderate rate embedding capacity under AWGN channel with varying noise variances. This achievement is important as the first step for both active and passive steganalysis is the detection of the existence of covert channel. This work has multiple contributions in the field of data hiding. Firstly, it is the first example of a data hiding method in which the trajectory of a VO is used. Secondly, this work has contributed towards improving steganographic security by providing new features: the coordinate location and semantic meaning of the object

Discrete Wavelet Transforms

The discrete wavelet transform (DWT) algorithms have a firm position in processing of signals in several areas of research and industry. As DWT provides both octave-scale frequency and spatial timing of the analyzed signal, it is constantly used to solve and treat more and more advanced problems. The present book: Discrete Wavelet Transforms: Algorithms and Applications reviews the recent progress in discrete wavelet transform algorithms and applications. The book covers a wide range of methods (e.g. lifting, shift invariance, multi-scale analysis) for constructing DWTs. The book chapters are organized into four major parts. Part I describes the progress in hardware implementations of the DWT algorithms. Applications include multitone modulation for ADSL and equalization techniques, a scalable architecture for FPGA-implementation, lifting based algorithm for VLSI implementation, comparison between DWT and FFT based OFDM and modified SPIHT codec. Part II addresses image processing algorithms such as multiresolution approach for edge detection, low bit rate image compression, low complexity implementation of CQF wavelets and compression of multi-component images. Part III focuses watermaking DWT algorithms. Finally, Part IV describes shift invariant DWTs, DC lossless property, DWT based analysis and estimation of colored noise and an application of the wavelet Galerkin method. The chapters of the present book consist of both tutorial and highly advanced material. Therefore, the book is intended to be a reference text for graduate students and researchers to obtain state-of-the-art knowledge on specific applications

Image adaptive watermarking using wavelet transform

The availability of versatile multimedia processing software and the far-reaching coverage of the interconnected networks have facilitated flawless copying, manipulations and distribution of the digital multimedia (digital video, audio, text, and images). The ever-advancing storage and retrieval technologies have also smoothed the way for large-scale multimedia database applications. However, abuses of these facilities and technologies pose pressing threats to multimedia security management in general, and multimedia copyright protection and content integrity verification in particular. Although cryptography has a long history of application to information and multimedia security, the undesirable characteristic of providing no protection to the media once decrypted has limited the feasibility of its widespread use. For example, an adversary can obtain the decryption key by purchasing a legal copy of the media but then redistribute the decrypted copies of the original. In response to these challenges; digital watermarking techniques have been proposed in the last decade. Digital watermarking is the procedure whereby secret information (the watermark) is embedded into the host multimedia content, such that it is: (1) hidden, i.e., not perceptually visible; and (2) recoverable, even after the content is degraded by different attacks such as filtering, JPEG compression, noise, cropping etc. The two basic requirements for an effective watermarking scheme, imperceptibility and robustness, conflict with each other. The main focus of this thesis is to provide good tradeoff between perceptual quality of the watermarked image and its robustness against different attacks. For this purpose, we have discussed two robust digital watermarking techniques in discrete wavelet (DWT) domain. One is fusion based watermarking, and other is spread spectrum based watermarking. Both the techniques are image adaptive and employ a contrast sensitivity based human visual system (HVS) model. The HVS models give us a direct way to determine the maximum strength of watermark signal that each portion of an image can tolerate without affecting the visual quality of the image. In fusion based watermarking technique, grayscale image (logo) is used as watermark. In watermark embedding process, both the host image and watermark image are transformed into DWT domain where their coefficients are fused according to a series combination rule that take into account contrast sensitivity characteristics of the HVS. The method repeatedly merges the watermark coefficients strongly in more salient components at the various resolution levels of the host image which provides simultaneous spatial localization and frequency spread of the watermark to provide robustness against different attacks. Watermark extraction process requires original image for watermark extraction. In spread spectrum based watermarking technique, a visually recognizable binary image is used as watermark. In watermark embedding process, the host image is transformed into DWT domain. By utilizing contrast sensitivity based HVS model, watermark bits are adaptively embedded through a pseudo-noise sequence into the middle frequency sub-bands to provide robustness against different attacks. No original image is required for watermark extraction. Simulation results of various attacks are also presented to demonstrate the robustness of both the algorithms. Simulation results verify theoretical observations and demonstrate the feasibility of the digital watermarking algorithms for use in multimedia standards

Recent Advances in Signal Processing

The signal processing task is a very critical issue in the majority of new technological inventions and challenges in a variety of applications in both science and engineering fields. Classical signal processing techniques have largely worked with mathematical models that are linear, local, stationary, and Gaussian. They have always favored closed-form tractability over real-world accuracy. These constraints were imposed by the lack of powerful computing tools. During the last few decades, signal processing theories, developments, and applications have matured rapidly and now include tools from many areas of mathematics, computer science, physics, and engineering. This book is targeted primarily toward both students and researchers who want to be exposed to a wide variety of signal processing techniques and algorithms. It includes 27 chapters that can be categorized into five different areas depending on the application at hand. These five categories are ordered to address image processing, speech processing, communication systems, time-series analysis, and educational packages respectively. The book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity

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

QUALITY-DRIVEN CROSS LAYER DESIGN FOR MULTIMEDIA SECURITY OVER RESOURCE CONSTRAINED WIRELESS SENSOR NETWORKS

The strong need for security guarantee, e.g., integrity and authenticity, as well as privacy and confidentiality in wireless multimedia services has driven the development of an emerging research area in low cost Wireless Multimedia Sensor Networks (WMSNs). Unfortunately, those conventional encryption and authentication techniques cannot be applied directly to WMSNs due to inborn challenges such as extremely limited energy, computing and bandwidth resources. This dissertation provides a quality-driven security design and resource allocation framework for WMSNs. The contribution of this dissertation bridges the inter-disciplinary research gap between high layer multimedia signal processing and low layer computer networking. It formulates the generic problem of quality-driven multimedia resource allocation in WMSNs and proposes a cross layer solution. The fundamental methodologies of multimedia selective encryption and stream authentication, and their application to digital image or video compression standards are presented. New multimedia selective encryption and stream authentication schemes are proposed at application layer, which significantly reduces encryption/authentication complexity. In addition, network resource allocation methodologies at low layers are extensively studied. An unequal error protection-based network resource allocation scheme is proposed to achieve the best effort media quality with integrity and energy efficiency guarantee. Performance evaluation results show that this cross layer framework achieves considerable energy-quality-security gain by jointly designing multimedia selective encryption/multimedia stream authentication and communication resource allocation

A new approach for improving transparency of audio watermarking.

Chen Benrong.Thesis (M.Phil.)--Chinese University of Hong Kong, 2003.Includes bibliographical references (leaves 125-130).Abstracts in English and Chinese.Chapter 1 --- Introduction --- p.1Chapter 1.1 --- What' s Watermarking --- p.1Chapter 1.2 --- "Information Hiding, Steganography, and Watermarking" --- p.3Chapter 1.3 --- History of Watermarking --- p.5Chapter 1.4 --- Importance of Digital Watermarking --- p.8Chapter 1.5 --- Objectives of the Thesis --- p.9Chapter 1.6 --- Thesis Outline --- p.10Chapter 2 --- Applications and Properties of Audio Watermarking --- p.12Chapter 2.1 --- Applications --- p.13Chapter 2.1.1 --- Ownership Identification and Proof --- p.13Chapter 2.1.2 --- Broadcast Monitoring --- p.16Chapter 2.1.3 --- Other Applications --- p.18Chapter 2.2 --- Properties --- p.19Chapter 2.2.1 --- Transparency --- p.20Chapter 2.2.2 --- Robustness --- p.20Chapter 2.2.3 --- Other Properties --- p.21Chapter 3 --- Possible Methods for Audio Watermarking --- p.24Chapter 3.1 --- Overview of Digital Audio Watermarking System --- p.25Chapter 3.2 --- Review of Current Methods --- p.27Chapter 3.2.1 --- Low Bit Coding --- p.27Chapter 3.2.2 --- Phase Coding --- p.28Chapter 3.2.3 --- Echo Coding --- p.29Chapter 3.2.4 --- Spread Spectrum Watermarking --- p.30Chapter 3.3 --- Other Related Approaches --- p.31Chapter 3.4 --- Outline of Proposed New Method --- p.33Chapter 4 --- Audio Watermarking System Based on Spread Spectrum --- p.36Chapter 4.1 --- Introduction --- p.36Chapter 4.2 --- Embedding and Detecting Information Bit --- p.39Chapter 4.2.1 --- General Embedding Process --- p.39Chapter 4.2.2 --- General Detection Process --- p.43Chapter 4.2.3 --- Pseudorandom Bit Sequences (PRBS) --- p.45Chapter 4.3 --- An Optimal Embedding Process --- p.48Chapter 4.3.1 --- Objective Metrics for Embedding Process --- p.48Chapter 4.3.2 --- Content Adaptive Embedding --- p.52Chapter 4.3.3 --- Determination of Frame Length L --- p.57Chapter 4.4 --- Requirement For Transparency Improvement --- p.58Chapter 5 --- Sample and Frame Selection For Transparency Improvement --- p.60Chapter 5.1 --- Introduction --- p.60Chapter 5.2 --- Sample Selection --- p.61Chapter 5.2.1 --- General Sample Selection --- p.62Chapter 5.2.2 --- Objective Evaluation Metrics --- p.65Chapter 5.2.3 --- Sample Selection For Transparency Improvement --- p.66Chapter 5.2.4 --- Theoretical Analysis of Sample Selection --- p.87Chapter 5.3 --- Frame Sclcction --- p.90Chapter 5.3.1 --- General Frame Selection --- p.91Chapter 5.3.2 --- Frame Selection For Transparency Improvement --- p.94Chapter 5.4 --- Watermark Information Retrieve --- p.103Chapter 6 --- Psychoacoustic Model For Robustness Verification --- p.105Chapter 6.1 --- Introduction of Human Auditory System --- p.106Chapter 6.1.1 --- Absolute Hearing Threshold --- p.106Chapter 6.1.2 --- Critical Bands --- p.108Chapter 6.1.3 --- Masking Effect --- p.111Chapter 6.2 --- Psychoacoustic Model of Human Auditory System --- p.112Chapter 6.3 --- Robustness Verification by Psychoacoustic Model Analysis --- p.117Chapter 7 --- Conclusions and Suggestions For Future Research --- p.121Chapter 7.1 --- Conclusions --- p.121Chapter 7.2 --- Suggestions For Future Research --- p.123Bibliography --- p.12

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