Entropy Based Robust Watermarking Algorithm

Tänu aina kasvavale multimeedia andmeedastus mahtudele Internetis, on esile kerkinud mured turvalisusest ja piraatlusest. Digitaalse meedia paljundamise ja muutmise maht on loonud vajaduse digitaalse meedia vesimärgistamise järgi. Selles töös on tutvustatud vastupidavaid vesimärkide lisamise algoritme, mis lisavad vesimärgid madala entroopiaga pildi osadesse. Välja pakutud algoritmides jagatakse algne pilt blokkidesse ning arvutatakse iga bloki entroopia. Kõikide blokkide keskmine entroopia väärtus valitakse künniseks, mille järgi otsustatakse, millistesse blokkidesse vesimärk lisada. Kõik blokid, mille entroopia on väiksem kui künnis, viiakse signaali sageduse kujule kasutades Discrete Wavelet Transform algoritmi. Madala sagedusega sagedusvahemikule rakendatakse Chirp Z-Transform algoritmi ja saadud tulemusele LU-dekompositsiooni või QR-dekompositsiooni. Singular Value Decomposition meetodi rakendamisel diagonaalmaatriksile, mis saadi eelmisest sammust, saadakse iga bloki vastav väärtus. Vesimärk lisatakse pildile, liites iga bloki arvutatud väärtusele vesimärgi Singular Value Decomposition meetodi tulemused. Kirjeldatud algoritme testiti ning võrreldi teiste tavapärast ning uudsete vesimärkide lisamise tehnoloogiatega. Kvantitatiivsed ja kvalitatiivsed eksperimendid näitavad, et välja pakutud meetodid on tajumatud ning vastupidavad signaali töötlemise rünnakutele.With growth of digital media distributed over the Internet, concerns about security and piracy have emerged. The amount of digital media reproduction and tampering has brought a need for content watermarking. In this work, multiple robust watermarking algorithms are introduced. They embed watermark image into singular values of host image’s blocks with low entropy values. In proposed algorithms, host image is divided into blocks, and the entropy of each block is calculated. The average of all entropies indicates the chosen threshold value for selecting the blocks in which watermark image should be embedded. All blocks with entropy lower than the calculated threshold are decomposed into frequency subbands using discrete wavelet transform (DWT). Subsequently chirp z-transform (CZT) is applied to the low-frequency subband followed by an appropriate matrix decomposition such as lower and upper decomposition (LUD) or orthogonal-triangular decomposition (QR decomposition). By applying singular value decomposition (SVD) to diagonal matrices obtained by the aforementioned matrix decompositions, the singular values of each block are calculated. Watermark image is embedded by adding singular values of the watermark image to singular values of the low entropy blocks. Proposed algorithms are tested on many host and watermark images, and they are compared with conventional and other state-of-the-art watermarking techniques. The quantitative and qualitative experimental results are indicating that the proposed algorithms are imperceptible and robust against many signal processing attacks

A Robust Color Image Watermarking Scheme Using Entropy and QR Decomposition

Internet has affected our everyday life drastically. Expansive volumes of information are exchanged over the Internet consistently which causes numerous security concerns. Issues like content identification, document and image security, audience measurement, ownership, copyrights and others can be settled by using digital watermarking. In this work, robust and imperceptible non-blind color image watermarking algorithm is proposed, which benefit from the fact that watermark can be hidden in different color channel which results into further robustness of the proposed technique to attacks. Given method uses some algorithms such as entropy, discrete wavelet transform, Chirp z-transform, orthogonal-triangular decomposition and Singular value decomposition in order to embed the watermark in a color image. Many experiments are performed using well-known signal processing attacks such as histogram equalization, adding noise and compression. Experimental results show that proposed scheme is imperceptible and robust against common signal processing attacks

A survey of digital image watermarking techniques

Watermarking, which belong to the information hiding field, has seen a lot of research interest recently. There is a lot of work begin conducted in different branches in this field. Steganography is used for secret conmunication, whereas watermarking is used for content protection, copyright management, content authentication and tamper detection. In this paper we present a detailed survey of existing and newly proposed steganographic and watenmarking techniques. We classify the techniques based on different domains in which data is embedded. Here we limit the survey to images only

Multiple image watermarking using the SILE approach

Digital copyright protection has attracted a great spectrum of studies. One of the optimistic techniques is digital watermarking. Many digital watermarking algorithms were proposed in recent literature. One of the highly addressed issues within the watermarking literature is robustness against attacks. Considering this major issue, we propose a new robust image watermarking scheme. The proposed watermarking scheme achieves robustness by watermarking several images simultaneously. It firstly splits the watermark (which is a binary logo) into multiple pieces and then embeds each piece in a separate image, hence, this technique is termed 'Multiple Images Watermarking'. The binary logo is generated by extracting unique features from all the images which have to be watermarked. This watermark is first permuted and then embedded using SILE algorithm [7]. Permutation is important step to uniformly distribute the unique characteristics acquired from multiple logos. The proposed watermarking scheme is robust against a variety of attacks including Gamma Correction, JPEG, JPEG2000, Blur, Median, Histogram Equalization, Contrast, Salt and Pepper, Resize, Crop, Rotation 90, Rotation 180, Projective, Row Column Blanking and Row Column Copying and Counterfeit attack

Robust watermarking and its applications to communication problems

Digital watermarking has recently gained an intense interest in research and applications. An invisible and secret signal, called watermark, is added to the host data. With the help of this watermark issuer of the data can be unveiled, unauthorised users can be identified, illicit copying can be avoided, any attempt to temper with the data can be detected and many other security services can be provided. In this thesis, the relations and differences between watermarking and communication systems are elaborated. Based on these results new methods for both watermarking and communication are derived. A new blind, robust and reversible watermarking scheme based on Code Division Multiple Access (CDMA) is presented in this thesis. Using this scheme watermark is arithmetically added to spatial domain or frequency domain. Watermark is extracted by using spreading codes only. Proposed watermarking scheme is simple, computationally efficient and can be applied to any image format. A novel idea that watermark can be part of the image is presented. By using watermark, which is a part of an image, digital watermarking can be used beyond simple security tasks. A part of an image is selected and embedded in the whole image as watermark. This watermarked image is attacked (transmitted or compressed). By using the extracted watermark and attacked selected part image quality can be assessed or jpeg quantization ratio can be estimated or even image can be equalized blindly. Furthermore, CDMA based watermarking is used to authenticate radio frequency signal. Spreaded watermark is added in the form of noise to the modulated radio frequency signal. If this noise is increased, watermarked signal automatically becomes a scrambled signal. Later watermark is extracted and by using reversibility of proposed scheme watermark is removed. Once the watermarked is removed original signal is restored, hence descrambled

A robust audio watermarking scheme based on reduced singular value decomposition and distortion removal

This paper presents a blind audio watermarking algorithm based on the reduced singular value decomposition(RSVD). A new observation on one of the resulting unitary matrices is uncovered. The proposed scheme manipulates coefficients based on this observation in order to embed watermark bits. To preserve audio fidelity a threshold- based distortion control technique is applied and this is further supplemented by distortion suppression utilizing psychoacoustic principles. Test results on real music signals show that this watermarking scheme is in the range of imperceptibility for human hearing, is accurate and also robust against MP3 compression at various bit rates as well as other selected attacks. The data payload is comparatively high compared to existing audio watermarking schemes

Image forgery detection using textural features and deep learning

La croissance exponentielle et les progrès de la technologie ont rendu très pratique le partage de données visuelles, d'images et de données vidéo par le biais d’une vaste prépondérance de platesformes disponibles. Avec le développement rapide des technologies Internet et multimédia, l’efficacité de la gestion et du stockage, la rapidité de transmission et de partage, l'analyse en temps réel et le traitement des ressources multimédias numériques sont progressivement devenus un élément indispensable du travail et de la vie de nombreuses personnes. Sans aucun doute, une telle croissance technologique a rendu le forgeage de données visuelles relativement facile et réaliste sans laisser de traces évidentes. L'abus de ces données falsifiées peut tromper le public et répandre la désinformation parmi les masses. Compte tenu des faits mentionnés ci-dessus, la criminalistique des images doit être utilisée pour authentifier et maintenir l'intégrité des données visuelles. Pour cela, nous proposons une technique de détection passive de falsification d'images basée sur les incohérences de texture et de bruit introduites dans une image du fait de l'opération de falsification. De plus, le réseau de détection de falsification d'images (IFD-Net) proposé utilise une architecture basée sur un réseau de neurones à convolution (CNN) pour classer les images comme falsifiées ou vierges. Les motifs résiduels de texture et de bruit sont extraits des images à l'aide du motif binaire local (LBP) et du modèle Noiseprint. Les images classées comme forgées sont ensuite utilisées pour mener des expériences afin d'analyser les difficultés de localisation des pièces forgées dans ces images à l'aide de différents modèles de segmentation d'apprentissage en profondeur. Les résultats expérimentaux montrent que l'IFD-Net fonctionne comme les autres méthodes de détection de falsification d'images sur l'ensemble de données CASIA v2.0. Les résultats discutent également des raisons des difficultés de segmentation des régions forgées dans les images du jeu de données CASIA v2.0.The exponential growth and advancement of technology have made it quite convenient for people to share visual data, imagery, and video data through a vast preponderance of available platforms. With the rapid development of Internet and multimedia technologies, performing efficient storage and management, fast transmission and sharing, real-time analysis, and processing of digital media resources has gradually become an indispensable part of many people’s work and life. Undoubtedly such technological growth has made forging visual data relatively easy and realistic without leaving any obvious visual clues. Abuse of such tampered data can deceive the public and spread misinformation amongst the masses. Considering the facts mentioned above, image forensics must be used to authenticate and maintain the integrity of visual data. For this purpose, we propose a passive image forgery detection technique based on textural and noise inconsistencies introduced in an image because of the tampering operation. Moreover, the proposed Image Forgery Detection Network (IFD-Net) uses a Convolution Neural Network (CNN) based architecture to classify the images as forged or pristine. The textural and noise residual patterns are extracted from the images using Local Binary Pattern (LBP) and the Noiseprint model. The images classified as forged are then utilized to conduct experiments to analyze the difficulties in localizing the forged parts in these images using different deep learning segmentation models. Experimental results show that both the IFD-Net perform like other image forgery detection methods on the CASIA v2.0 dataset. The results also discuss the reasons behind the difficulties in segmenting the forged regions in the images of the CASIA v2.0 dataset

A New Digital Video Watermarking Using Decimated Wavelet and Principle Component Analysis in YCbCr Domain

Digital watermarking is a technology used for security and for the copyright protection of digital media application. In this letter, we introduced “A New Digital Video Watermarking Using Decimated Wavelet and Principle Component Analysis in YCbCr domain”. First, the input video stream will be divided into number of frames and then select one frame to embed the information into it. Now convert it into YCbCr color space and apply DWT followed by PCA to get the watermarked frame then replace this frame with the original frame to obtain the watermarked video. It has also tested for various attacks such asRST, cropping, compression, filtering and Gaussian noise successfully with reduced bit error. Peak signal to noise ratio (PSNR) and structural similarity index (SSIM) used to measure the quality of watermarked frame. Simulated results had shown that the proposed algorithm gives more superior results and higher imperceptibility over existing algorithm in terms of quality metrics