Affine invariant image watermarking using intensity probability density-based Harris Laplace detector

Feature point based image watermarking against geometric distortions has attracted great attention in recent years. However, for the state-of-the-art intensity based feature points detectors, the feature points often gather at textured portions of the image or on the edges where the change of intensity is significant, so that many feature points capture the same portion of the image, which makes the watermark be vulnerable to local geometric distortions. In this paper, we propose an affine invariant image watermarking scheme with good visual quality and reasonable resistance toward local geometric distortions, which utilizes the intensity probability density-based Harris–Laplace detector. Firstly, the uniform and robust feature points are extracted by utilizing modified Harris–Laplace detector, in which the intensity probability density gradient is used instead of intensity gradient. Then, the affine invariant local ellipse regions (LERs) are constructed adaptively according to the variation of local intensity probability density. Finally, the digital watermark is embedded into the affine invariant LERs in nonsubsampled contourlet transform (NSCT) domain by modulating the lowpass NSCT coefficients. By binding the watermark with the affine invariant LERs, the watermark detection can be done without synchronization error. Experimental results show that the proposed image watermarking is not only invisible and robust against common image processing operations such as sharpening, noise adding, and JPEG compression, but also robust against the global affine transforms and local geometric distortions.     

Digital watermarking robust to geometric distortions.

In this paper, we present two watermarking approaches that are robust to geometric distortions. The first approach is based on image normalization, in which both watermark embedding and extraction are carried out with respect to an image normalized to meet a set of predefined moment criteria. We propose a new normalization procedure, which is invariant to affine transform attacks. The resulting watermarking scheme is suitable for public watermarking applications, where the original image is not available for watermark extraction. The second approach is based on a watermark resynchronization scheme aimed to alleviate the effects of random bending attacks. In this scheme, a deformable mesh is used to correct the distortion caused by the attack. The watermark is then extracted from the corrected image. In contrast to the first scheme, the latter is suitable for private watermarking applications, where the original image is necessary for watermark detection. In both schemes, we employ a direct-sequence code division multiple access approach to embed a multibit watermark in the discrete cosine transform domain of the image. Numerical experiments demonstrate that the proposed watermarking schemes are robust to a wide range of geometric attacks.     

Discrete Multiwavelet–Based Video Watermarking Scheme Using SURF

This paper proposes a robust, imperceptible block‐based digital video watermarking algorithm that makes use of the Speeded Up Robust Feature (SURF) technique. The SURF technique is used to extract the most important features of a video. A discrete multiwavelet transform (DMWT) domain in conjunction with a discrete cosine transform is used for embedding a watermark into feature blocks. The watermark used is a binary image. The proposed algorithm is further improved for robustness by an error‐correction code to protect the watermark against bit errors. The same watermark is embedded temporally for every set of frames of an input video to improve the decoded watermark correlation. Extensive experimental results demonstrate that the proposed DMWT domain video watermarking using SURF features is robust against common image processing attacks, motion JPEG2000 compression, frame averaging, and frame swapping attacks. The quality of a watermarked video under the proposed algorithm is high, demonstrating the imperceptibility of an embedded watermark.     

基于归一化和Bessel–Fourier矩的鲁棒水印算法

为了增强水印的抗几何攻击能力,提出了一种基于归一化和Bessel-Fourier矩的鲁棒水印算法。首先对图像进行归一化,使图像的Bessel-Fourier矩具有旋转、缩放和平移(RST)不变性;然后通过使用Bessel-Fourier多项式直接将水印添加到图像的空域强度中,嵌入强度由一个迭代特征修改和验证程序控制,可以避免在水印嵌入和检测过程中引入错误。大量的实验结果表明,本文提出的水印算法对几何攻击以及一般的信号处理具有很好的鲁棒性。     

A new video watermarking algorithm based on 1D DFT and Radon transform

In this paper, we propose a new video watermarking algorithm based on the 1D DFT (one-dimensional discrete Fourier transform) and Radon transform. The 1D DFT for a video sequence generates an ideal domain, in which the spatial information is still kept and the temporal information is obtained. With detailed analysis and calculation, we choose the frames with highest temporal frequencies to embed the fence-shaped watermark pattern in the Radon transform domain of the selected frames. The adaptive embedding strength for different locations keeps the fidelity of the watermarked video. The performance of the proposed algorithm is evaluated by video compression standard H.264 with three different bit rates; geometric attacks such as rotation, translation, and aspect-ratio changes; and other attacks like frame drop, frame swap, spatial filtering, noise addition, lighting change, and histogram equalization. The main contributions of this paper are the introduction of the 1D DFT along temporal direction for watermarking that enables the robustness against video compression, and the Radon transform-based watermark embedding and extraction that produces the robustness against geometric transformations. One of the most important advantages of this video watermarking algorithm is its simplicity and practicality.     

基于帧间相关性的盲视频数字水印算法

提出了一种在原始视频中嵌入水印的算法。嵌入的水印由2部分组成:标志水印和信息水印。首先从一段原始视频里随机选出若干视频帧,在这些帧的像素平面亮度分量上固定位置嵌入标志水印,再根据密钥选取其他若干图像块在其离散余弦变换(DCT)直流系数中嵌入信息水印。然后在整段视频的每一小段中重复嵌入水印。提取水印时,只需从整段视频中截取足够包含完整信息水印的一小段视频,通过搜索标志水印快速地选出包含水印信息的帧。然后利用水印帧与前后相邻视频帧之间内容的高度相关性,得到嵌入水印位置像素值的估计,与包含水印信息帧相应位置做比较,提取出水印信息,实现了水印的盲提取。实验结果表明本算法能够抵抗压缩、缩放、帧删除/插入等各种攻击,具有较强的健壮性。     

Performance analysis for geometrical attack on digital image watermarking

We present a technique for irreversible watermarking approach robust to affine transform attacks in camera, biomedical and satellite images stored in the form of monochrome bitmap images. The watermarking approach is based on image normalisation in which both watermark embedding and extraction are carried out with respect to an image normalised to meet a set of predefined moment criteria. The normalisation procedure is invariant to affine transform attacks. The result of watermarking scheme is suitable for public watermarking applications, where the original image is not available for watermark extraction. Here, direct-sequence code division multiple access approach is used to embed multibit text information in DCT and DWT transform domains. The proposed watermarking schemes are robust against various types of attacks such as Gaussian noise, shearing, scaling, rotation, flipping, affine transform, signal processing and JPEG compression. Performance analysis results are measured using image processing metrics.     

Localized image watermarking in spatial domain resistant to geometric attacks

Watermark robustness to geometric attacks is still a challenging research field. In this paper, a novel robust image watermarking scheme is proposed for resisting such attacks. Watermark synchronization is first achieved by local invariant regions which can be generated using scale normalization and image feature points. The watermark is embedded into all the local regions repeatedly in spatial domain. During embedding, each circular region is first divided into homocentric cirque regions. Then the watermark bits are embedded by quantizing each cirque region into an “odd” or “even” region using odd–even quantization. In the decoder, an odd–even detector (OED) is designed to extract the watermark from the distorted image directly. Localized embedding achieves good invisibility and repeated insertion enhances watermark robustness. Simulation results show that the proposed scheme is robust to both geometric attacks and traditional signal processing attacks.     

一种在原始视频帧中嵌入的鲁棒的数字水印

该文提出的在原始视频帧中的扩频水印方案,使用二值图像作为水印,采用每帧索引的办法,并且利用相邻帧的统计相关性来嵌入水印。对于丢帧、帧重组以及共谋攻击有很强的鲁棒性。水印提取时不需要用到原始视频。文中对该方案进行了详细的介绍,并给出了仿真实验结果。     

Tchebichef矩在图像数字水印技术中的应用

提出了一种利用原始图像的Tchebichef矩来增加水印顽健性的方法,即利用原始图像的一个或多个Tchebichef矩的值来估计水印图像所经过的几何变换的参数以及图像增强等图像处理操作的参数,并将这一过程作为水印检测的预处理过程。实验中将多种不同的水印信息在不同的图像处理域(包括DWT、DCT、FFT以及空间域等)实现水印信息的嵌入。为了检测这种估计算法的顽健性,本文实验中的几何攻击是由Stirmark产生的。计算机模拟实验证明这种估计方法简单,估计精度很高,增加了图像水印技术对几何攻击的顽健性,而且可在任何处理域中实现,具有很好的实用价值。1     

Robust semi-blind video watermarking based on frame-patch matching

In this paper, we present a frame-patch matching based robust semi-blind video watermarking using KAZE feature. The KAZE feature is employed for matching the feature points of frame-patch with those of all frames in video for detecting the embedding and extracting regions. In our method, the watermark information is embedded in Discrete Cosine Transform (DCT) domain of randomly generated blocks in the matched region. In the extraction process, we synchronize the embedded region from the distorted video by using KAZE feature matching. Based on the matched KAZE feature points, RST (rotation, scaling, translation) parameters are estimated and the watermark information can be successfully extracted. Experimental results show that our proposed method is robust against geometrical attacks, video processing attacks, temporal attacks, and so on.     

基于Tchebichef不变矩的多比特抗几何攻击图像盲水印算法

现有的大多数水印算法对旋转、平移和尺度变换等几何攻击的鲁棒性比较差,微小的几何攻击都有能导致水印检测器失效,因此水印算法对几何攻击具有鲁棒性非常重要。本文提出了一种基于Tchebichef不变矩实现的多比特几何攻击不变性图像盲水印算法。文中具体介绍了Tchebichef不变矩的构造方法,水印是事先产生的与原始图像无关的信号,嵌入过程中将水印嵌入到图像的Tchebichef不变矩中实现几何攻击不变性。水印检测过程中采用独立分量分析技术实现真正意义上的多比特水印盲检测。文中具体分析了所提出的水印算法的计算复杂度,实验过程中采用通用水印测试软件Stirmark对所提出的水印算法进行鲁棒性测试,实验数据说明这种水印算法对Stirmark具有很好的鲁棒性。     

基于关键帧和小波变换的盲视频水印算法

针对现有视频水印算法在抗几何攻击能力方面的一些不足,提出一种基于关键帧和小波变换的盲视频水印算法.依据视频帧间差欧氏距离提取视频关键帧并分块,结合人类视觉系统特性,从关键帧不同的块中选择亮度敏感性和纹理敏感性最高的块构成三维体块,进行三维小波变换,将置乱的水印图像以不同的嵌入强度嵌入到小波系数的低频区域,利用阈值门限实现水印的盲提取.结果表明,该算法提高了水印嵌入容量,对于针对视频水印的攻击具有较好的不可见性和稳健性.     

DWT-based high-capacity blind video watermarking, invariant to geometrical attacks

The paper describes a high-capacity blind video watermarking system invariant to geometrical attacks such as shift, rotation, scaling and cropping. A spatial domain reference watermark is used to obtain invariance to geometric attacks by employing image registration techniques to determine and invert the attacks. A second, high-capacity watermark, which carries the data payload, is embedded in the wavelet domain according to a human visual system model. This is protected by a state-of-the-art error correction code (turbo code). For a false detection probability of 10/sup -8/, the proposed system is invariant to scaling up to 180%, rotation up to 70/spl deg/, and arbitrary aspect ratio changes up to 200% on both axes. Furthermore, the system is virtually invariant to any shifting, cropping, or combined shifting and cropping. The system is also robust to MPEG2 compression, even when combined with shifting and cropping.     

Study on semantic-based video watermarking method

A new video watermarking method for the Audio Video coding Standard (AVS) is proposed. According to human visual masking properties, this method determines the region of interest for watermark embedding by analyzing video semantics, and generates dynamic robust watermark according to video motion semantics, and embeds watermarks in the Intermediate Frequency (IF) Discrete Cosine Transform (DCT) coefficients of the luminance sub-block prediction residual in the region of interest. This method controls watermark embedding strength adaptively by video textures semantics. Experiments show that this method is robust not only to various conventional attacks, but also to re-frame, frame cropping, frame deletion and other video-specific attacks.     

基于奇偶量化的空域抗几何攻击图像水印算法

数字水印对几何攻击的鲁棒性问题一直没有得到很好的解决,该文提出了一种能够抵抗RST(旋转、缩放、平移)攻击,局部剪切以及常规信号处理攻击的多比特图像水印算法。该文利用尺度不变特征变换(SIFT)进行水印信号的同步;设计了一种圆环形的水印模式,并在空域采用奇偶量化嵌入水印;并设计了一种奇偶检测器提取水印。实验结果表明该算法能获得很好的图像质量,且能十分有效地抵抗各种几何攻击以及常规的压缩,滤波等攻击。     

L/M-fold image resizing in block-DCT domain using symmetric convolution

Image resizing is to change an image size by upsampling or downsampling of a digital image. Most still images and video frames on digital media are given in a compressed domain. Image resizing of a compressed image can be performed in the spatial domain via decompression and recompression. In general, resizing of a compressed image in a compressed domain is much faster than that in the spatial domain. We propose a novel approach to resize images with L/M resizing ratio in the discrete cosine transform (DCT) domain, which exploits the multiplication-convolution property of DCT (multiplication in the spatial domain corresponds to symmetric convolution in the DCT domain). When an image is given in terms of its 8/spl times/8 block-DCT coefficients, its resized image is also obtained in 8/spl times/8 block-DCT coefficients. The proposed approach is computationally fast and produces visually fine images with high PSNR.     

Blind MPEG-2 video watermarking in DCT domain robust against scaling

Watermarking techniques that need no original information during watermark detection, known as blind watermarking, are more desirable than informed ones for practical usage and convenience in watermark extraction. A blind MPEG-2 watermarking technique operating in the DCT (discrete cosine transform) domain is presented, which is generally robust against arbitrary ratio scaling, provided that turbo codes are used for error correction. The method can be directly applied to other block-DCT-based video compression techniques. The main advantage of the scheme is its simplicity, blindness and the ability to tailor the watermark payload in a trade-off with other watermark requirements. As synchronisation is automatically obtained from the frames in the scaled video itself, a connection between the source and the target video is not necessary for watermarking detection     

Utilizing neighborhood coefficient correlation: a new image watermarking technique robust to singular and hybrid attacks

A new blind digital image watermarking algorithm with watermark embedded in discrete cosine transform (DCT) coefficients is presented in this paper. The proposed scheme exploits correlation between DCT coefficients in neighborhood blocks for embedding. The watermark is embedded by modifying two DCT coefficients, one pertaining to a block in which watermark bit (0 or 1) is to be embedded and the other corresponding to the selected neighborhood block. Both the selected coefficients are modified by a modification factor so that the difference between the pair of coefficients is brought to a predefined zone. This difference between two DCT coefficients is used to extract watermark. The proposed technique has been tested for different attacks like JPEG compression, rotation, cropping, filtering, gaussian noise, salt and pepper noise, histogram equalization etc. It has been observed that the scheme is highly robust not only for the above mentioned attacks used singularly, but also for different possible combinations of simultaneous attacks. A comparison of the proposed technique with some state of art existing algorithms reveals that our scheme provides better results in terms of quality of watermarked images, payload and robustness.     

Robust Video Watermarking of H.264/AVC

A robust video watermarking scheme of the state-of-the-art video coding standard H.264/AVC is proposed in this brief. 2-D 8-bit watermarks such as detailed company trademarks or logos can be used as inconvertible watermark for copyright protection. A grayscale watermark pattern is first modified to accommodate the H.264/AVC computational constraints, and then embedded into video data in the compressed domain. With the proposed method, the video watermarking scheme can achieve high robustness and good visual quality without increasing the overall bit-rate. Experimental results show that our algorithm can robustly survive transcoding process and strong common signal processing attacks, such as bit-rate reduction, Gaussian filtering and contrast enhancement