Blind colour image watermarking techniques in hybrid domain using least significant bit and slantlet transform

Colour image watermarking has attracted a lot of interests since the last decade in tandem with the rapid growth of internet and its applications. This is due to increased awareness especially amongst netizens to protect digital assets from fraudulent activities. Many research efforts focused on improving the imperceptibility or robustness of both semi-blind and non-blind watermarking in spatial or transform domain. The results so far have been encouraging. Nonetheless, the requirements of the watermarking applications are varied in terms of imperceptibility, robustness and capacity. Ironically, limited studies concern on the authenticity and blind watermarking. Hence, this study presents two new blind RGB image watermarking techniques called Model1 and Model2 in hybrid domain using Least Significant Bit (LSB) insertion and Slantlet Transform (SLT). The models share similar pre-processing and LSB insertion stages but differ in SLT approach. In addition, two interrelated watermarks known as main watermark (MW) and sub-watermark (SW) are also utilized. Firstly, the RGB cover image is converted into YCbCr colour space and then split up into three components namely, Y, Cb and Cr. Secondly, the Cb component is selected as a cover for the MW embedding using the LSB substitution to attain a Cb-watermarked image (CbW). Thirdly, the Cr component is chosen and converted into the transform domain using SLT, and is subsequently decomposed into two paths: three-level sub-bands for Model1 and two-level sub-bands for Model2. For each model, the sub-bands are then used as a cover for sub-watermark embedding to generate a Cr-watermarked image (CrW). Following that, the Y component, CbW and CrW are combined to obtain a YCbCr-watermarked image. Finally, the image is reverted to RGB colour space to attain the actual watermarked image (WI). Upon embedding, the MW and SW are extracted from WI. The extraction process is similar to the above embedding except it is accomplished in a reverse order. Experimental results which utilized the standard dataset with fifteen well-known attacks revealed that, among others: Model1 has produced high imperceptibility, moderate robustness and good capacity, with Peak Signal-to-Noise Ratio (PSNR) rose to 65dB, Normalized Cross Correlation (NCC) moderated at 0.80, and capacity was 15%. Meanwhile, Model2, as per designed, performed positively in all aspects, with NCC strengthened to 1.00, capacity jumped to 25% and PSNR softened at 55dB but still on the high side. Interestingly, in terms of authenticity, Model2 performed impressively albeit the extracted MW has been completely altered. Overall, the models have successfully fulfilled all the research objectives and also markedly outperformed benchmark watermarking techniques

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

Schémas de tatouage d'images, schémas de tatouage conjoint à la compression, et schémas de dissimulation de données

In this manuscript we address data-hiding in images and videos. Specifically we address robust watermarking for images, robust watermarking jointly with compression, and finally non robust data-hiding.The first part of the manuscript deals with high-rate robust watermarking. After having briefly recalled the concept of informed watermarking, we study the two major watermarking families : trellis-based watermarking and quantized-based watermarking. We propose, firstly to reduce the computational complexity of the trellis-based watermarking, with a rotation based embedding, and secondly to introduce a trellis-based quantization in a watermarking system based on quantization.The second part of the manuscript addresses the problem of watermarking jointly with a JPEG2000 compression step or an H.264 compression step. The quantization step and the watermarking step are achieved simultaneously, so that these two steps do not fight against each other. Watermarking in JPEG2000 is achieved by using the trellis quantization from the part 2 of the standard. Watermarking in H.264 is performed on the fly, after the quantization stage, choosing the best prediction through the process of rate-distortion optimization. We also propose to integrate a Tardos code to build an application for traitors tracing.The last part of the manuscript describes the different mechanisms of color hiding in a grayscale image. We propose two approaches based on hiding a color palette in its index image. The first approach relies on the optimization of an energetic function to get a decomposition of the color image allowing an easy embedding. The second approach consists in quickly obtaining a color palette of larger size and then in embedding it in a reversible way.Dans ce manuscrit nous abordons l’insertion de données dans les images et les vidéos. Plus particulièrement nous traitons du tatouage robuste dans les images, du tatouage robuste conjointement à la compression et enfin de l’insertion de données (non robuste).La première partie du manuscrit traite du tatouage robuste à haute capacité. Après avoir brièvement rappelé le concept de tatouage informé, nous étudions les deux principales familles de tatouage : le tatouage basé treillis et le tatouage basé quantification. Nous proposons d’une part de réduire la complexité calculatoire du tatouage basé treillis par une approche d’insertion par rotation, ainsi que d’autre part d’introduire une approche par quantification basée treillis au seind’un système de tatouage basé quantification.La deuxième partie du manuscrit aborde la problématique de tatouage conjointement à la phase de compression par JPEG2000 ou par H.264. L’idée consiste à faire en même temps l’étape de quantification et l’étape de tatouage, de sorte que ces deux étapes ne « luttent pas » l’une contre l’autre. Le tatouage au sein de JPEG2000 est effectué en détournant l’utilisation de la quantification basée treillis de la partie 2 du standard. Le tatouage au sein de H.264 est effectué à la volée, après la phase de quantification, en choisissant la meilleure prédiction via le processus d’optimisation débit-distorsion. Nous proposons également d’intégrer un code de Tardos pour construire une application de traçage de traîtres.La dernière partie du manuscrit décrit les différents mécanismes de dissimulation d’une information couleur au sein d’une image en niveaux de gris. Nous proposons deux approches reposant sur la dissimulation d’une palette couleur dans son image d’index. La première approche consiste à modéliser le problème puis à l’optimiser afin d’avoir une bonne décomposition de l’image couleur ainsi qu’une insertion aisée. La seconde approche consiste à obtenir, de manière rapide et sûre, une palette de plus grande dimension puis à l’insérer de manière réversible

A Fast And Efficient Method To Protect Color Images

International audienceIn this paper, we propose a method to embed the color information of an image in a corresponding grey-level image. The objective of this work is to allow free access to the grey-level image and give color image access only if you own a secret key. This method is made of three major steps which are a fast color quantization, an optimized ordering and an adapted data hiding. The principle is to build an index image which is, in the same time, a semantically intelligible grey-level image. In order to obtain this particular index image, which should be robust to data hiding, a layer running algorithm is proceeded to sort the K colors of the palette. The major contributions of this paper are the fast color quantization, the optimized layer running algorithm, the color palette compression and the adapted data hiding