Méthodes de tatouage robuste pour la protection de l imagerie numerique 3D

La multiplication des contenus stéréoscopique augmente les risques de piratage numérique. La solution technologique par tatouage relève ce défi. En pratique, le défi d une approche de tatouage est d'atteindre l équilibre fonctionnel entre la transparence, la robustesse, la quantité d information insérée et le coût de calcul. Tandis que la capture et l'affichage du contenu 3D ne sont fondées que sur les deux vues gauche/droite, des représentations alternatives, comme les cartes de disparité devrait également être envisagée lors de la transmission/stockage. Une étude spécifique sur le domaine d insertion optimale devient alors nécessaire. Cette thèse aborde les défis mentionnés ci-dessus. Tout d'abord, une nouvelle carte de disparité (3D video-New Three Step Search- 3DV-SNSL) est développée. Les performances des 3DV-NTSS ont été évaluées en termes de qualité visuelle de l'image reconstruite et coût de calcul. En comparaison avec l'état de l'art (NTSS et FS-MPEG) des gains moyens de 2dB en PSNR et 0,1 en SSIM sont obtenus. Le coût de calcul est réduit par un facteur moyen entre 1,3 et 13. Deuxièmement, une étude comparative sur les principales classes héritées des méthodes de tatouage 2D et de leurs domaines d'insertion optimales connexes est effectuée. Quatre méthodes d'insertion appartenant aux familles SS, SI et hybride (Fast-IProtect) sont considérées. Les expériences ont mis en évidence que Fast-IProtect effectué dans la nouvelle carte de disparité (3DV-NTSS) serait suffisamment générique afin de servir une grande variété d'applications. La pertinence statistique des résultats est donnée par les limites de confiance de 95% et leurs erreurs relatives inférieurs er <0.1The explosion in stereoscopic video distribution increases the concerns over its copyright protection. Watermarking can be considered as the most flexible property right protection technology. The watermarking applicative issue is to reach the trade-off between the properties of transparency, robustness, data payload and computational cost. While the capturing and displaying of the 3D content are solely based on the two left/right views, some alternative representations, like the disparity maps should also be considered during transmission/storage. A specific study on the optimal (with respect to the above-mentioned properties) insertion domain is also required. The present thesis tackles the above-mentioned challenges. First, a new disparity map (3D video-New Three Step Search - 3DV-NTSS) is designed. The performances of the 3DV-NTSS were evaluated in terms of visual quality of the reconstructed image and computational cost. When compared with state of the art methods (NTSS and FS-MPEG) average gains of 2dB in PSNR and 0.1 in SSIM are obtained. The computational cost is reduced by average factors between 1.3 and 13. Second, a comparative study on the main classes of 2D inherited watermarking methods and on their related optimal insertion domains is carried out. Four insertion methods are considered; they belong to the SS, SI and hybrid (Fast-IProtect) families. The experiments brought to light that the Fast-IProtect performed in the new disparity map domain (3DV-NTSS) would be generic enough so as to serve a large variety of applications. The statistical relevance of the results is given by the 95% confidence limits and their underlying relative errors lower than er<0.1EVRY-INT (912282302) / SudocSudocFranceF

High capacity data embedding schemes for digital media

High capacity image data hiding methods and robust high capacity digital audio watermarking algorithms are studied in this thesis. The main results of this work are the development of novel algorithms with state-of-the-art performance, high capacity and transparency for image data hiding and robustness, high capacity and low distortion for audio watermarking.En esta tesis se estudian y proponen diversos métodos de data hiding de imágenes y watermarking de audio de alta capacidad. Los principales resultados de este trabajo consisten en la publicación de varios algoritmos novedosos con rendimiento a la altura de los mejores métodos del estado del arte, alta capacidad y transparencia, en el caso de data hiding de imágenes, y robustez, alta capacidad y baja distorsión para el watermarking de audio.En aquesta tesi s'estudien i es proposen diversos mètodes de data hiding d'imatges i watermarking d'àudio d'alta capacitat. Els resultats principals d'aquest treball consisteixen en la publicació de diversos algorismes nous amb rendiment a l'alçada dels millors mètodes de l'estat de l'art, alta capacitat i transparència, en el cas de data hiding d'imatges, i robustesa, alta capacitat i baixa distorsió per al watermarking d'àudio.Societat de la informació i el coneixemen

A no-reference optical flow-based quality evaluator for stereoscopic videos in curvelet domain

Most of the existing 3D video quality assessment (3D-VQA/SVQA) methods only consider spatial information by directly using an image quality evaluation method. In addition, a few take the motion information of adjacent frames into consideration. In practice, one may assume that a single data-view is unlikely to be sufficient for effectively learning the video quality. Therefore, integration of multi-view information is both valuable and necessary. In this paper, we propose an effective multi-view feature learning metric for blind stereoscopic video quality assessment (BSVQA), which jointly focuses on spatial information, temporal information and inter-frame spatio-temporal information. In our study, a set of local binary patterns (LBP) statistical features extracted from a computed frame curvelet representation are used as spatial and spatio-temporal description, and the local flow statistical features based on the estimation of optical flow are used to describe the temporal distortion. Subsequently, a support vector regression (SVR) is utilized to map the feature vectors of each single view to subjective quality scores. Finally, the scores of multiple views are pooled into the final score according to their contribution rate. Experimental results demonstrate that the proposed metric significantly outperforms the existing metrics and can achieve higher consistency with subjective quality assessment

Peningkatan Kapasitas dan Perbaikan Kualitas Penyisipan Audio Data Hiding dengan Newton’s Divided-Difference Interpolating Polynomials

Steganografi adalah sebuah cara mengubah data secara tidak terdeteksi untuk menyisipkan sebuah pesan pada data tersebut. Secara umum, system steganografi terdiri dari dua komponen utama yaitu encoder dan decoder. Saat ini penelitian mengenai steganografi telah banyak dilakukan, namun kebanyakan metode yang ada hanya diterapkan berkas citra dan hanya sedikit penelitian yang terkait dengan penyisipan berkas rahasia pada berkas audio. Beberapa metode yang ada juga memiliki kelemahan dimana berkas yang digunakan sebagai media penyisipan tidak dapat dikembalikan seperti semula, serta metode yang ada masih menggunakan berkas tambahan untuk location maps dan juga masalah kapasitas penyisipan yang masih dirasa kurang optimum, sehinga diperlukan suatu metode yang bersifat reversible yang mampu menghilangkan berkas tambahan location maps. Penelitian ini mengusulkan metode baru penyisipan data yang mengadopsi dari proses pembentukan kurva dari suatu data, hal ini didasarkan karena berkas audio memiliki karakateristik dan bentuk yang dihasilkan dari berkas audio menyerupai dengan kurva pada sekumpulan data. Metode yang diusulkan juga berperan sebagai pivoting point yang digunakan titik acuan penyisipan sebagai pengganti location maps. Dalam skenario uji coba, dataset diperoleh dari IRMAS dataset. Ada 5 jenis instrumen musik yang digunakan dan 3 genre musik sebagai media cover dalam penelitian ini yaitu country-folk, klasik, dan pop-rock. Durasi berkas audio yang digunakan pada masing-masing jenis musik selama 3 detik. Format dari berkas pembawa yang digunakan berekstensi .wav, hal ini dipilih karena berkas audio format wav tanpa ada proses kompresi. Berkas yang digunakan sebagai data payload merupakan berkas teks yang diperoleh dari teks generator. Ada beberapa hal yang diuji pada penelitian ini antara lain kapasistas maksimum payload yang disisipkan, pengaruh jenis instrumen, pengaruh genre musik, serta proses reduksi signal. Signal noise to ratio dan perhitungan kapasitas digunakan untuk mengevaluasi hasil penyisispan sesuai dengan metode yang diusulkan. Hasil penelitian yaitu kapasitas maksium diperoleh pada audio 3 sebesar 1262296 bit dengan genre pop-rock, instrumen cello. Kualitas terbaik meningkat 33.8% dari penelitian sebelumnya menggunakan audio genre country-folk dan instrumen human voice. ================================================================ Steganography is a way to change the undetected data to hide a message into it. Generally, the steganography system consists of two main components; namely encoder and decoder. Currently researches on steganography have been widely practiced, but most of them are only applied in image files and only some researches that related to the hiding data of secret files in audio files. Some of existing methods still have disadvantages e.g.; the files that used as insertion media can’t be able to restored as the original one, it still used additional files for maps location, and the problem of hidden capacity is still not optimum yet. In order to solve the disadvantages, it is required a reversible method which is able to eliminate the additional maps location. This research proposes a new method of data hiding which is adopted from the curve formation process of a data. It is based on the audio file exhibits the characteristics and also the result form of the audio beam resembles to the curve in the data set. The proposed method also become as a pivoting point which is used as a reference of insertion point instead of maps location. In trial scenario, the dataset is derived from the IRMAS dataset. In this research, there are 5 types of musical instruments that is used and 3 genres of music as media cover; country-folk, classic, and pop-rock. The duration for audio files that is used in each type of music is 3 seconds. The format of the bearer file used .wav extension, because the wav format in audio file without any compression process. The file that is used as payload data is a text file which is obtained from the generator text. In this research, some parameters like the maximum payload capacity inserted; the influence of instrument type; the influence of the music genre; and the process of signal reduction are tested. According to the proposed method, the signal noise to ratio and the capacity calculation are used to evaluate the results of the dispersion. The final result is obtained the maximum capacity in audio 3 equal to 1262296 bit on pop-rock genre, cello instrument. The best quality increased 33.8% from the previous research which is used country-folk genre and human voice instruments audio

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

Efficient and Robust Video Steganography Algorithms for Secure Data Communication

Over the last two decades, the science of secretly embedding and communicating data has gained tremendous significance due to the technological advancement in communication and digital content. Steganography is the art of concealing secret data in a particular interactive media transporter such as text, audio, image, and video data in order to build a covert communication between authorized parties. Nowadays, video steganography techniques are important in many video-sharing and social networking applications such as Livestreaming, YouTube, Twitter, and Facebook because of noteworthy developments in advanced video over the Internet. The performance of any steganography method, ultimately, relies on the imperceptibility, hiding capacity, and robustness against attacks. Although many video steganography methods exist, several of them lack the preprocessing stages. In addition, less security, low embedding capacity, less imperceptibility, and less robustness against attacks are other issues that affect these algorithms. This dissertation investigates and analyzes cutting edge video steganography techniques in both compressed and raw domains. Moreover, it provides solutions for the aforementioned problems by proposing new and effective methods for digital video steganography. The key objectives of this research are to develop: 1) a highly secure video steganography algorithm based on error correcting codes (ECC); 2) an increased payload video steganography algorithm in the discrete wavelet domain based on ECC; 3) a novel video steganography algorithm based on Kanade-Lucas-Tomasi (KLT) tracking and ECC; 4) a robust video steganography algorithm in the wavelet domain based on KLT tracking and ECC; 5) a new video steganography algorithm based on the multiple object tracking (MOT) and ECC; and 6) a robust and secure video steganography algorithm in the discrete wavelet and discrete cosine transformations based on MOT and ECC. The experimental results from our research demonstrate that our proposed algorithms achieve higher embedding capacity as well as better imperceptibility of stego videos. Furthermore, the preprocessing stages increase the security and robustness of the proposed algorithms against attacks when compared to state-of-the-art steganographic methods

Multimedia Forensics

This book is open access. Media forensics has never been more relevant to societal life. Not only media content represents an ever-increasing share of the data traveling on the net and the preferred communications means for most users, it has also become integral part of most innovative applications in the digital information ecosystem that serves various sectors of society, from the entertainment, to journalism, to politics. Undoubtedly, the advances in deep learning and computational imaging contributed significantly to this outcome. The underlying technologies that drive this trend, however, also pose a profound challenge in establishing trust in what we see, hear, and read, and make media content the preferred target of malicious attacks. In this new threat landscape powered by innovative imaging technologies and sophisticated tools, based on autoencoders and generative adversarial networks, this book fills an important gap. It presents a comprehensive review of state-of-the-art forensics capabilities that relate to media attribution, integrity and authenticity verification, and counter forensics. Its content is developed to provide practitioners, researchers, photo and video enthusiasts, and students a holistic view of the field

Multimedia Forensics

This book is open access. Media forensics has never been more relevant to societal life. Not only media content represents an ever-increasing share of the data traveling on the net and the preferred communications means for most users, it has also become integral part of most innovative applications in the digital information ecosystem that serves various sectors of society, from the entertainment, to journalism, to politics. Undoubtedly, the advances in deep learning and computational imaging contributed significantly to this outcome. The underlying technologies that drive this trend, however, also pose a profound challenge in establishing trust in what we see, hear, and read, and make media content the preferred target of malicious attacks. In this new threat landscape powered by innovative imaging technologies and sophisticated tools, based on autoencoders and generative adversarial networks, this book fills an important gap. It presents a comprehensive review of state-of-the-art forensics capabilities that relate to media attribution, integrity and authenticity verification, and counter forensics. Its content is developed to provide practitioners, researchers, photo and video enthusiasts, and students a holistic view of the field

Entropy in Image Analysis II

Image analysis is a fundamental task for any application where extracting information from images is required. The analysis requires highly sophisticated numerical and analytical methods, particularly for those applications in medicine, security, and other fields where the results of the processing consist of data of vital importance. This fact is evident from all the articles composing the Special Issue "Entropy in Image Analysis II", in which the authors used widely tested methods to verify their results. In the process of reading the present volume, the reader will appreciate the richness of their methods and applications, in particular for medical imaging and image security, and a remarkable cross-fertilization among the proposed research areas