Khaled Loukhaoukha

A secure image encryption algorithm based on Rubik's cube principle

In the past few years, several encryption algorithms based on chaotic systems have been proposed as means to protect digital images against cryptographic attacks. These encryption algorithms typically use relatively small key spaces and thus offer limited security, especially if they are one-dimensional. In this paper, we proposed a novel image encryption algorithm based on Rubiks cube principle. The original image is scrambled using the principle of Rubiks cube. Then, XOR operator is applied to rows and columns of the scrambled image using two secret keys. Finally, the experimental results and security analysis show that the proposed image encryption scheme not only can achieve good encryption and perfect hiding ability but also can resist exhaustive attack, statistical attack, and differential attack.

Hybrid watermarking algorithm based on SVD and lifting wavelet transform for ownership verification

In this paper, we propose a hybrid robust digital watermarking algorithm based on singular value decomposition (SVD) and lifting wavelet transform (LWT). In contrast to other watermarking algorithms based on wavelet transforms which exploit the human visual system (HVS), proposed method does not require to use HVS characteristics. After decomposing the cover image into a two-level lifting wavelet transform, we compute the inverse LWT of a selected subband (SB). The watermark embedding procedure is done by modifying singular values. Experimental results demonstrate that this method is robust against several attacks such as: noise addition, histogram equalization, gamma correction, JPEG compression, cropping, rotation and randomly line and column removal.

Security of ownership watermarking of digital images based on singular value decomposition

Recently watermarking algorithms of digital images based on singular value decomposition (SVD) have been proposed. Most SVD-based watermarking techniques use singular values as the embedding watermark information. These SVD-based techniques are advantageous for watermarking images since slight changes in the singular values do not significantly affect the image quality. However, it has been reported that these SVD-based watermarking algorithms, as implemented, suffer from a very high probability of false positive detections of watermarks. The false positive detection vulnerability of two recent SVD-based watermarking schemes is exposed. Two solutions are proposed to mitigate this vulnerability without changing the design principle of these watermarking algorithms.

Comments on “A digital watermarking scheme based on singular value decomposition and tiny genetic algorithm”

Abstract In the recent paper entitled “A digital watermarking scheme based on singular value decomposition and tiny genetic algorithm” by C.-C. Lai (2011) [1] , a robust digital image watermarking scheme based on singular value decomposition and a tiny genetic algorithm is proposed. This comment shows that this watermarking scheme is fundamentally flawed in that the extracted watermark is not the embedded watermark but determined by the reference watermark.

A robust SVD-based image watermarking using a multi-objective particle swarm optimization

The major objective in developing a robust digital watermarking algorithm is to obtain the highest possible robustness without losing the visual imperceptibility. To achieve this objective, we proposed in this paper an optimal image watermarking scheme using multi-objective particle swarm optimization (MOPSO) and singular value decomposition (SVD) in wavelet domain. Having decomposed the original image into ten sub-bands, singular value decomposition is applied to a chosen detail sub-band. Then, the singular values of the chosen sub-band are modified by multiple scaling factors (MSF) to embed the singular values of watermark image. Various combinations of multiple scaling factors are possible, and it is difficult to obtain optimal solutions. Thus, in order to achieve the highest possible robustness and imperceptibility, multi-objective optimization of the multiple scaling factors is necessary. This work employs particle swarm optimization to obtain optimum multiple scaling factors. Experimental results of the proposed approach show both the significant improvement in term of imperceptibility and robustness under various attacks.

Multi-objective genetic algorithm optimization for image watermarking based on singular value decomposition and lifting wavelet transform

In this paper, a new optimal watermarking scheme based on singular value decomposition (SVD) and lifting wavelet transform (LWT) using multi-objective genetic algorithm optimization (MOGAO) is presented. The singular values of the watermark is embedded in a detail subband of host image. To achieve the highest possible robustness without losing watermark transparency, multiple scaling factors (MSF) are used instead of single scaling factor (SSF). Determining the optimal values of the MSFs is a difficult problem. However, to find this values a multi-objective genetic algorithm optimization is used. Experimental results show a much improved performance in term of transparency and robustness of the proposed method compared to others methods.

A new reliable optimized image watermarking scheme based on the integer wavelet transform and singular value decomposition for copyright protection

Although image watermarking schemes based on singular value decomposition (SVD) demonstrate high robustness and imperceptibility, they are exposed to the false positive problem (FPP). This drawback mostly occurs when embedding steps depend on singular values while singular vectors are used as secret keys. In this study, a new reliable SVD-based image watermarking scheme that uses integer wavelet transform (IWT) is proposed to overcome FPP and fulfil all watermarking requirements. Unlike in other schemes, the S and V matrices of the watermark are used as secret keys, whereas the S singular vector of the watermark is embedded into the singular values of the host image. The additional secret key is obtained from the watermarked image during the embedding process to increase security and avoid FPP completely. To improve the robustness, as well as achieve balance between robustness and imperceptibility, multi-objective ant colony optimization (MOACO) is utilized to find the optimal scaling factors, namely, multiple zooming factors. Results of the robustness, imperceptibility, and reliability tests demonstrate that the proposed IWT-SVD-MOACO scheme outperforms several previous schemes and avoids FPP completely.

Turbo code using adaptive puncturing for pixel domain distributed video coding

Distributed video coding is a research field which brings together error coding techniques along with video compression ones. Its core part is a Slepian-Wolf encoder which often involves turbo codes because of their strong error correction capabilities. The turbo encoder generates parity bits which are sent to refine the side information constructed at the decoder by interpolation using the neighboring key frames already received. For bit rate flexibility, these parity bits are punctured and sent gradually upon request until the receiver can correctly decode the frame. In this work, we introduce a novel distributed video coding scheme with adaptive puncturing that sends more parity bits when the virtual channel is noisy and less parity bit when it is not the case. Considerable compression performance improvement over the puncturing techniques used in literature is reported.

A new image watermarking algorithm based on wavelet transform

In this paper, we proposed a new non blind robust digital watermarking algorithm for embedding binary image watermark in grayscale images. For embedding procedure, three levels discrete wavelet transform of cover image is computed. Afterward the watermark image is added in the high-high (HH), low-high (LH) and high-low (HL) subbands using a threshold coefficients. The low-low (LL) subband coefficients are not used in embedding procedure because that the human visual system (HVS) is less sensitive to the small change in edges and textures of image. Comparing the performance of our method to other watermarking methods, the proposed method show good performance in terms of invisibility and robustness. Experimental results demonstrate that the proposed method has a good robustness against several attacks such as: noise addition, histogram equalization, Gamma correction, JPEG compression, cropping and randomly line and column removal.

Progressive distributed video coding with multiple passes for side information update

Distributed video coding is a new video paradigm that transfers the computational bulk from video encoders to decoders. Thus, the scenario of video transmission involving inexpensive encoders and a powerful central decoder would be possible. In a previous work, the authors have proposed a novel distributed video coding scheme with progressive decoding. The proposed architecture considers a chessboard structure for block grouping. A subset of blocks are first sent, decoded and then used to update the side information. Then, the remaining blocks are sent and decoded using the updated and more accurate side information. This progressive technique with two groups of blocks shows an improvement up to 1.7 dB over the conventional DVC architecture. In this paper, we extend the progressive architecture by splitting the frame into three and four groups of blocks rather than only two groups. Further improvement up to 0.4 dB over the progressive architecture with only two groups is obtained.