Thai Duy Hien

Robust multi-logo watermarking by RDWT and ICA

This paper proposes a new approach to watermarking multimedia products by redundant discrete wavelet transform (RDWT) and independent component analysis (ICA). For watermark security, embedded logo watermarks are encrypted to random noise signal. To embed logo watermarks, the original image is decomposed by RDWT, and watermarks are embedded into middle frequency at LH and HL sub-bands. The perceptual model is applied with a stochastic multiresolution model for adaptive watermark embedding. This is based on computation of a noise visibility function (NVF) which has local image properties. We also propose an intelligent ICA-based detector which directly extracts watermarks in spatial domain. A novel characteristic of this detection is that it does not require the transformation process to extract the watermark. The experimental results show that logo watermarks are extracted perfectly, and also demonstrate the robustness of the method.

ROBUST DIGITAL WATERMARKING BASED ON PRINCIPAL COMPONENT ANALYSIS

We propose a robust digital watermarking technique based on Principal Component Analysis (PCA) and evaluate the effectiveness of the method against some watermark attacks. In this proposed method, watermarks are embedded in the PCA domain and the method is closely related to DCT or DWT based frequency-domain watermarking. The orthogonal basis functions, however, are determined by data and they are adaptive to the data. The presented technique has been successfully evaluated and compared with DCT and DWT based watermarking methods. Experimental results show robust performance of the PCA based method against most prominent attacks.

Curvelet-Domain Image Watermarking Based on Edge-Embedding

A new curvelet-based watermarking technique is presented in this paper, in which watermark signals are selected to be a gray-scale logo image. The curvelet transform was developed in order to represent edges along curves much more efficiently than the traditional transforms. We apply the transform to watermarking and evaluate the effectiveness of the method. Our watermarking algorithm embeds a watermark in curvelet coefficients which are selected by a criterion whether they contain as much edge information as possible. We evaluated the effectiveness of the method against some watermark attacks. Experiment results show that our new method yields quite good visual quality in watermarked images, and is robust to typical signal processing attacks such as compression, cropping, adding noise and filtering.

PCA Based Digital Watermarking

This work evaluates a novel watermarking method based on Principle Component Analysis and effectiveness of the method to some watermark attacks. A PCA is used on a block by block basis to decorrelate the image pixel, watermarks are added in the Principle Components of an image. A theoretical description of the method is included together with experimental results in order to validate the methodology presented. Simulation shows the performance of the method to be robust for image cropping and some attacks such as additive noise, low pass filtering, median filtering, and jpeg compression. This research presents a new approach to watermarking fields with good performance in image cropping, and enhancement to this system with respect to robustness against various attacks is under investigation.

ICA-based robust logo image watermarking

Digital watermarking is a technology proposed to address the issue of copyright protection for digital content. In this paper, we have developed a new robust logo watermarking technique. Watermark embedding is performed in the wavelet domain of the host image. The human visual system (HVS) is exploited by building a spatial mask based on stochastic model for content adaptive digital watermarking. Independent component analysis (ICA) is introduced to extract the logo watermark. Our simulation results suggest that ICA can be used to extract exactly watermark that was hidden in image and show that our system performs robustness well under various important types of attacks.

DCT Watermarking Optimization by Genetic Programming

Embedding a digital watermark in an electronic document is proving to be a feasible solution for multimedia copyright protection and authentication pur- poses. However, the balance between the watermark robustness and its invisibility has always been a challenge for watermarkers. Consequently, it was necessary to use a powerful computation system that can guarantee the watermarking requirements. In this end, we propose to apply genetic programming to digital watermarking. In this work, we are presenting a new watermarking scheme in DCT domain based on genetic programming (GP). It is an optimizing structure which permits to develop automatically the embedding equation of a DCT algorithm possessing a high PSNR value and a good robustness. Simulation results were satisfactory.

Multichannel Color Image Watermarking Using PCA Eigenimages

In the field of image watermarking, research has been mainly focused on gray image watermarking, whereas the extension to the color case is usually accom- plished by marking the image luminance, or by processing color channels separately. In this paper we propose a new digital watermarking method of three bands RGB color images based on Principal Component Analysis (PCA). This research, which is an extension of our earlier work, consists of embedding the same digital water- mark into three RGB channels of the color image based on PCA eigenimages. We evaluated the effectiveness of the method against some watermark attacks. Exper- imental results show that the performance of the proposed method against most prominent attacks is good.

RDWT/ICA for image authentication

This paper proposes a new approach to watermarking multimedia products by redundant wavelet transform (RDWT) and independent component analysis (ICA). For watermark security, embedded logo watermarks are encrypted to random noise signal. To embed logo watermarks, the original image is decomposed by RDWT, and watermarks are embedded into middle frequency subbands. The perceptual model is applied with a stochastic multi-resolution model for adaptive watermark embedding. This is based on computation of a noise visibility function (NVF) which has local image properties. We also propose an intelligent ICA-based detector which directly extracts watermarks in spatial domain. A novel characteristic of this detection is that it does not require the transformation process to extract the watermark. The experimental results show that logo watermarks are extracted perfectly, and also demonstrate the robustness of the method

A Robust Logo Multiresolution Watermarking Based on Independent Component Analysis Extraction

This paper proposes a novel blind logo multi-resolution watermarking technique based on independent component analysis (ICA) for extraction. To exploit the human visual system (HVS) and the robustness, a perceptual model is applied with a stochastic approach based on noise visibility function (NVF) for adaptive watermarking algorithm. A logo watermark is embedded by modifying middle-frequency sub-bands of wavelet transform. The new detection technique based on ICA is introduced during the extraction phase to ensure a blind watermark. The proposed algorithm is checked for the robustness to several compression algorithms such as Jpeg, jpeg 2000, SPIHT, EZW, and principal components analysis (PCA) based compression and also robust against various image and digital processing operators.

RDWT Domain Watermarking based on Independent Component Analysis Extraction

We present a new digital watermarking in which redundant wavelet transform (RDWT) is applied for watermark embedding and independent component analysis (ICA) is used to extract the watermark. By using RDWT, a large logo watermark can be embedded into transform coefficients. The advantage of using large logo is the ability to carry redundant information about copyright, increasing the robustness. In the embedding procedure, the watermark is embedded in RDWT domain. However, in the extraction procedure, the watermark is directly extracted from the watermarked image in spatial domain by an ICA-based detector. The experiment shows that the proposed scheme produces less image distortion than conventional DWT and is robust against Jpeg/Jpeg2000/SPIHT image compression and other attacks.