This paper presents a novel technique for embedding a digital watermark into video frames based on motion vectors and discrete wavelet transform (DWT). In the proposed scheme, the binary image watermark is divided into blocks and each watermark block is embedded several times in each selected video frame at different locations. The block-based motion estimation algorithm is used to select the video frame blocks having the greatest motion vectors magnitude. The DWT is applied to the selected frame blocks, and then, the watermark block is hidden into these blocks by modifying the coefficients of the Horizontal sub-bands (HL). Adding the watermark at different locations in the same video frame makes the scheme more robust against different types of attacks. The method was tested on different types of videos. The average peak signal to noise ratio (PSNR) and the normalized correlation (NC) are used to measure the performance of the proposed method. Experimental results show that the proposed algorithm does not affect the visual quality of video frames and the scheme is robust against a variety of attacks.

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Multiresolution Video Watermarking Algorithm Exploiting the Block-Based Motion Estimation

This paper is to investigate a novel framework of robust video watermarking based on the statistical model with robustness against multiple attacks. The main contribution is threefold. First, the Laplacian distribution is proposed to model each naive video frame, referring to as the original frame; meanwhile the noisy frame, referring to as the one with adding Gaussian-distributed noise, is modeled using the Gaussian distribution. Second, we propose a novel mechanism of embedding watermark by artificially adding noise or not, corresponding to watermark bit 1 or 0. Third, it is proposed to cast the problem of watermark extraction into the framework of hypothesis testing theory. In the ideal context, with knowing all the model parameters, the Likelihood Ratio Test (LRT) is smoothly established with verifying the feasibility of the designed watermark extraction based on the statistical models. In the case of estimating model parameters, we propose to design the Generalized Likelihood Ratio Test (GLRT) to deal with the practical problem of watermark extraction. Finally, compared with some prior arts, extensive experimental results show that our proposed novel framework of robust video watermarking can achieve the high video quality with robustness against various attacks such as re-scaling, cropping, and compression.

A Novel Framework of Robust Video Watermarking Based on Statistical Model

Objectives: The present work proposes a secure and robust video watermarking algorithm to detect the camcorder piracy using Discrete Cosine Transform (DCT) and Schur Decomposition Methods/Analysis: Separate watermark for each video used to improve security The watermark is further secured using scrambling by Arnold transform and then dividing it into subparts These scrambled watermark chunks embedded into audio sequence and video frames using robust technique DCT and Schur decomposition The security has been improved with randomness in frame selection block selection Recovered information from extracted watermark can be used to authenticate the owner Findings: Experimental results show that the proposed algorithm is not only robust to various attacks but also highly secure Perceptual quality of watermarked frame has been compared with the original frame The Peak Signal to Noise Ratio (PSNR) is 4921 dB for MBmp4 video and 4888 dB for GTmp4 video file after embedding watermark Robustness of watermarked video has been tested against various signal processing, video processing attacks and camcorder attack Extracted watermark is compared with original watermark and Normalized cross correlation (NK) value is calculated, which is coming nearly 1 The security has been strengthened with randomness in frame selection, block selection, Scrambling and division of the watermark A Watermark is embedded in audio sequence and video frames Novelty/Improvement: Position of pirate is estimated by comparing original video frames with watermarked video frames Mean Absolute Error is 28 cm

Secure, Robust Video Watermarking to Prevent Camcorder Piracy

Digital watermarking algorithms for stereo image and video have been simple extensions of monoscopic watermarking methods to two views, and have not considered the aspects of the human visual system which are particular to stereo perception. One key aspect is binocular suppression, which says that high quality image data (for example with sharp edges) presented to one eye can suppress low quality information (for example, blurriness) which is simultaneously presented to the other eye, so that the combined subjective visual effect is one of high quality. We exploit this phenomenon by inserting watermark bits into different portions of the left and right image views, so that high quality in a region on one view suppresses the visibility of the watermark in the corresponding region of the other view. Tests with human observers confirm the visual superiority of the approach.

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Binocular suppression based visual masking model for stereo image watermarking

In healthcare information systems, medical data is very important for diagnosis. Most of the health institutions store their patients’ data on third-party servers. Therefore, its security is very important, since the advent of advanced multimedia and communication technology, whereby digital contents are manipulated, copied, and duplicated without leaving any trace. In this paper, a reversible watermarking technique is applied to the patients’ data (ultrasound image sequence). Since the traditional watermarking schemes can experience some permanent distortions that are not acceptable in the medical application. Thus, a reversible watermarking technique has been used, which can not only secure the ultrasound image sequence but also restore the original sequence back. For watermark embedding, the magnitude and phase angles of motion vectors of the image sequence are used that are obtained by using Full-Search block-based motion estimation algorithm. Before applying the motion estimation algorithm and watermark embedding, the histogram pre-processing is performed to avoid underﬂow/overﬂow. Unlike other state-of-the-art watermarking schemes that are reported in the last decades, the experimental results show that the proposed algorithm is simple, provides a much larger embedding capacity and better quality of the watermarked image sequence.

/pdf/protection-of-ultrasound-image-sequence-employing-motion-2uhclyd152.pdf

Protection of Ultrasound Image Sequence: Employing Motion Vector Reversible Watermarking

According to the features of DCT-based and DFT-based video watermark algorithms against attacks and considering 3D video structural characteristic, a new robust blind video watermark algorithm in transform domain combining with 3D video correlation is proposed. DCT-based watermark and DFT-based watermark are embedded in left and right images of a video frame using opposite embedding rules, and the watermark can be extracted by integrating 3D video correlation, and more robust watermark is extracted from the DCT-based watermark and the DFT-based watermark by comparing their performance. The algorithm can significantly improve the robustness of 3D video watermark against resolution attack and coding attack. The experimental results show that the proposed algorithm has excellent performance against resolution attack and coding attack, and is obviously better than DCT-based and DFT-based algorithms.

Ding Hai-yang

Papers

Robust Blind Video Watermark Algorithm in Transform Domain Combining with 3D Video Correlation