Information Hiding and Applications

Applications for robust watermarking is one of the major branches in digital rights management (DRM) systems. Based on existing experiences to assess how good one robust watermarking is, it is generally agreed that three parameters or requirements, including the quality of watermarked contents, the survivability of extracted watermark after deliberate or unintentional attacks, and the number of bits embedded, need to be considered. However, performances relating to these three parameters conflict with each other, and the trade off must be searched for. In this chapter, we take these requirements into consideration, and we can find the optimized combination among the three parameters. With the aid of genetic algorithm, we design an applicable system that would obtain the good quality, acceptable survivability, and reasonable capacity after watermarking. Simulation results present the effectiveness in practical implementation and possible application of the proposed algorithm.

A robust video watermarking method is described that can embed watermarks immune to not only rotation, scaling, and clipping and translation but also random geometric distortion and any of their combinations. It can detect watermarks without any search for canceling the effect of random distortion. Rotation, scale, and translation are canceled by searching for the angle, size, and origin of the original picture. The search for the angle and size is combinatorial and independent of the search for the origin. That is, the angle and size of the target picture can be restored without necessarily restoring the picture’s origin. Furthermore, the search for the origin is divided into horizontal and vertical searches that can be carried out independently. The number of searches is thus drastically reduced, making the processing time short enough for practical application. Watermark strength is controlled using an improved human visual system model for processing color information. This is done in the L*u*v* space, where human-perceived degradation of picture quality can be measured in terms of Euclidean distance. The watermarks are actually embedded and detected in the YUV space, where watermarks can be detected more reliably than that in the L*u*v* space. Experimental evaluation using actual video samples demonstrated that the proposed method can embed watermarks immune to rotation, scaling, clipping and translation, random distortion, and combinations thereof while maintaining picture quality.

The technique of digital image inpainting is used to repair scratches or stains in aged images or films. Furthermore, inpainting can also be used to remove selected objects from a video. Video inpainting is more difficult than image inpainting because video inpainting considers two or more frames with the same or different backgrounds. In order to prevent an unexpected user from eliminating objects in a video, the technique of data embedding is used to embed object data into the video. This paper proposes a framework that combines object segmentation and data embedding. The experimental results show that the stego video carries object data with high visual quality and the lost objects can be clearly restored from the inpainted stego video.

Data hiding is widely used for concealing secrets in images so that senders can securely transfer these secrets to the receivers. In data embedding schemes, the image quality, hiding capacity, and compression ratio as well as the security of the hidden data are all critical issues. Instead of using traditional data encryption techniques to encrypt secret data in the preprocessing phase, this paper proposes a hybrid data embedding scheme using SMVQ and gray-code computation. The experimental results demonstrate that this proposed scheme can achieve reasonable image quality in decoded images and a reasonable compression ratio while guaranteeing the security of the hidden data.

Digital watermarking techniques have been explored extensively since its first appearance in the 1990s. However, watermark robustness to geometric attacks is still an open problem. The past decade has witnessed a significant improvement in the understanding of geometric attacks and how watermarks can survive such attacks. In this chapter, we will introduce a set of image watermarking schemes which can resist both geometric attacks and traditional signal processing attacks simultaneously. These schemes follow a uniform framework, which is based on the detection of scale-space feature points. We call it the scale-space feature point based watermarking, SSFW for short. Scale-space feature points have been developed recently for pattern recognition applications. This kind of feature points are commonly invariant to rotation, scaling and translation (RST), therefore they naturally fit into the framework of geometrically robust image watermarking. Scale-space feature points are typically detected from the scale space of the image. As a result, we will first introduce the scale space theory and how the feature points can be extracted. The basic principles on how the scale-space feature points can be adapted for watermark synchronization are then discussed in detail. Subsequently, we will present several content-based watermark embedding and extraction methods which can be directly implemented based on the synchronization scheme. A detailed watermarking scheme which combines scale-invariant feature transform (SIFT) and Zernike moments is then presented for further understanding of SSFW. Watermarking schemes based on the SSFW framework have the following advantages: (a) Good invisibility. The Peak Signal to Noise Ratio (PSNR) value is typically higher than 40dB. (b) Good robustness. These schemes can resist both signal processing attacks and geometric attacks, such as JPEG compression, image filtering, added noise, RST attacks, locally cropping as well as some combined attacks.

With the rapid technological advancement in the development, storage and transmission of digital content, watermarking applications are both growing in number and becoming complex. This has prompted the use of computational intelligence in watermarking, especially for thwarting attacks. In this context, we describe the development of a new watermarking system based on intelligent perceptual shaping of a digital watermark using Genetic Programming (GP). The proposed approach utilizes optimum embedding strength together with appropriate DCT position selection and information pertaining to conceivable attack in order to achieve superior tradeoff in terms of the two conflicting properties in digital watermarking, namely, robustness and imperceptibility. This tradeoff is achieved by developing superior perceptual shaping functions using GP, which learn the content of a cover image by exploiting the sensitivities/insensitivities of Human Visual System (HVS) as well as attack information. The improvement in imperceptibility and bit correct ratio after attack are employed as the multi-objective fitness criteria in the GP search.

This chapter presents a secure and simple content-based digital signature method for verifying the image authentication under JPEG, JPEG2000 compression and scaling based on a novel concept named lowest authenticable difference (LAD). The whole method, which is extended from the crypto-based digital signature scheme, mainly consists of statistical analysis and signature generation/verification. The invariant features, which are generated from the relationship among image blocks in the spatial domain, are coded and signed by the sender’s private key to create a digital signature for each image, regardless of the image size. The main contributions of the proposed scheme are: (1) only the spatial domain is adopted during feature generation and verification, making domain transformation process unnecessary; (2) more non-malicious manipulated images (JPEG, JPEG2000 compressed and scaled images) than related studies can be authenticated by LAD, achieving a good trade-off of image authentication between fragile and robust under practical image processing; (3) non-malicious manipulation is clearly defined to meet closely the requirements of storing images or sending them over the Internet. The related analysis and discussion are presented. The experimental results indicate that the proposed method is feasible and effective.

The unicast method is a more efficient scheme to transmit multimedia data to massive users to compare with the multicast method. However, the ease of delivery of multimedia data may cause the copyrights to be violated easily, and the fingerprinting scheme is one of effective means for conquering this problem. The fingerprinting process often generates the multimedia contents into many different versions, which have to be transmitted via the unicast method. In this chapter, we propose a new genetic fingerprinting scheme for copyright protection of multicast media. In this method, the encryption and decryption keys, which aim at scrambling and descrambling multimedia contents, are first produced with genetic algorithms. Next, multimedia data are then encrypted and multicast to all clients. At the same time, a secure channel is employed to unicast a designated decryption key to each client. When a user deploys the designated key to decrypt the received data, a corresponding fingerprint would be embedded into the contents. Once upon the reception of the fingerprinted content, the embedded fingerprint can be extracted shortly, and the copyright can be confirmed and assured. Experimental results demonstrate that the proposed method can transmit multimedia data to clients effectively and cause only a slight degradation in perceptual quality.

With the development of image halftoning techniques and computer networks, a large quantity of digital halftone images are produced and transmitted in the Internet. Meanwhile, hiding data in images becomes a powerful approach for covert communications, copyright protection, owner announcement, content authentication, traitor tracing, etc. This chapter proposes two look-up table based methods to hide data in the cover media of halftone images. Both of them belong to lossless data hiding techniques, i.e., not only the secret data but also the original cover image can be accurately recovered in data extraction when the stego image is intact. Besides, an application example of the proposed method in lossless content authentication is illustrated. Furthermore, a data capacity enhancement strategy is introduced based on a statistical property of error diffused halftone image micro structure.

Digital information and data are transmitted more often over the Internet now than ever. Free-access digital multimedia communication unfortunately provides virtually unprecedented opportunities to pirate copyrighted material. Therefore, the idea of using a digital watermark to detect and trace copyright violations has stimulated significant interests among engineers, scientists, lawyers, artists and publishers. In this chapter, we present robust high-capacity digital watermarking techniques based on genetic algorithm (GA) and chaotic map. A GA-based technique is presented to correct the rounding errors. The fundamental is to adopt a fitness function for choosing the best chromosome which determines the conversion rule of real numbers into integers during the cosine transformation. We develop a block-based chaotic map, which outperforms the traditional one by breaking local spatial similarity, to increase the amount of significant coefficients in the transformed image. We demonstrate the superiority of the proposed scheme in terms of better embedding capacity and lower message error rate. Furthermore, we show the proposed algorithm works well under some image-processing distortions, such as the JPEG compression, Gaussian noise, and low-pass filter.