Automatic stereoscopic video object-based watermarking using qualified significant wavelet trees

In this paper a fully automatic scheme for embedding visually recognizable watermark patterns to video objects is proposed. The architecture consists of 3 main modules. During the first module unsupervised video object extraction is performed, by analyzing stereoscopic pairs of frames. In the second module each video object is decomposed into three levels with ten subbands, using the Shape Adaptive Discrete Wavelet Transform (SA-DWT) and three pairs of subbands are formed (HL3 , HL2), (LH3, LH2) and (HH3, HH2). Next Qualified Significant Wavelet Trees (QSWTs) are estimated for the specific pair of subbands with the highest energy content. QSWTs are derived from the Embedded Zerotree Wavelet (EZW) algorithm and they are high-energy paths of wavelet coefficients. Finally during the third module, visually recognizable watermark patterns are redundantly embedded to the coefficients of the highest energy QSWTs and the inverse SA-DWT is applied to provide the watermarked video object. Performance of the proposed video object watermarking system is tested under various signal distortions such as JPEG lossy compression, sharpening, blurring and adding different types of noise. Furthermore the case of transmission losses for the watermarked video objects is also investigated. Experimental results on real life video objects indicate the efficiency and robustness of the proposed schemeFacultad de Informátic

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

An Energy-Efficient and Reliable Data Transmission Scheme for Transmitter-based Energy Harvesting Networks

Energy harvesting technology has been studied to overcome a limited power resource problem for a sensor network. This paper proposes a new data transmission period control and reliable data transmission algorithm for energy harvesting based sensor networks. Although previous studies proposed a communication protocol for energy harvesting based sensor networks, it still needs additional discussion. Proposed algorithm control a data transmission period and the number of data transmission dynamically based on environment information. Through this, energy consumption is reduced and transmission reliability is improved. The simulation result shows that the proposed algorithm is more efficient when compared with previous energy harvesting based communication standard, Enocean in terms of transmission success rate and residual energy.This research was supported by Basic Science Research Program through the National Research Foundation by Korea (NRF) funded by the Ministry of Education, Science and Technology(2012R1A1A3012227)

Fuzzy Logic

The capability of Fuzzy Logic in the development of emerging technologies is introduced in this book. The book consists of sixteen chapters showing various applications in the field of Bioinformatics, Health, Security, Communications, Transportations, Financial Management, Energy and Environment Systems. This book is a major reference source for all those concerned with applied intelligent systems. The intended readers are researchers, engineers, medical practitioners, and graduate students interested in fuzzy logic systems

An Automatic Scheme for Stereoscopic Video Object-based Watermarking Using Qualified Significant Wavelet Trees

In this paper a fully automatic system for embedding visually recognizable watermark patterns to video objects is proposed. The architecture consists of 3 main modules. During the first module unsupervised video object extraction is performed, by analyzing stereoscopic pairs of frames. Then each video object is decomposed into three levels with ten subbands, using the Discrete Wavelet Transform (DWT) and three pairs of subbands are formed (HL 3 , HL 2 ), (LH 3 , LH 2 ) and (HH 3 , HH 2 ). Next Qualified Significant Wavelet Trees (QSWTs) are estimated for the specific pair of subbands that contains the highest energy content compared to the other two pairs. QSWTs are derived from the Embedded Zerotree Wavelet (EZW) algorithm and they are high-energy coefficient paths within the selected pair of subbands. Finally during the third module, visually recognizable watermark patterns are redundantly embedded to the coefficients of the highest energy QSWTs and the inverse DWT is applied to provide the watermarked video object. The performance of the proposed video object watermarking system is tested under various signal distortions such as JPEG lossy compression, sharpening, blurring and adding different types of noise. Experimental results on real life stereoscopic images are presented to indicate the efficiency and robustness of the proposed scheme

Personality Identification from Social Media Using Deep Learning: A Review

Social media helps in sharing of ideas and information among people scattered around the world and thus helps in creating communities, groups, and virtual networks. Identification of personality is significant in many types of applications such as in detecting the mental state or character of a person, predicting job satisfaction, professional and personal relationship success, in recommendation systems. Personality is also an important factor to determine individual variation in thoughts, feelings, and conduct systems. According to the survey of Global social media research in 2018, approximately 3.196 billion social media users are in worldwide. The numbers are estimated to grow rapidly further with the use of mobile smart devices and advancement in technology. Support vector machine (SVM), Naive Bayes (NB), Multilayer perceptron neural network, and convolutional neural network (CNN) are some of the machine learning techniques used for personality identification in the literature review. This paper presents various studies conducted in identifying the personality of social media users with the help of machine learning approaches and the recent studies that targeted to predict the personality of online social media (OSM) users are reviewed