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In this paper, we propose a new digital watermarking algorithm in encrypted image based on compressive sensing measurements and 2-D discrete wavelet transform (DWT). Firstly, we process the original image through 2-D DWT to highlight the important part and unimportant part. For the important LL2 coefficient, before encrypting it by the traditional stream cipher, we divide it into blocks, and mark the blocks to get a sequence as the watermark position key. For other wavelet coefficients, we select two different compressive sensing measurement matrices to simultaneously encrypt and compress them, respectively. Then we embed a watermark into the high frequency coefficient measurements except HH1 section based on the watermark position key. Finally, the watermarked image is scrambled to enhance the security. In this algorithm, compressive sensing is adopted for compression and encryption, and watermark is embedded in the measurements values. It can not only increase the watermark embedding capacity and robustness, but also utilize the reconstruction characteristic of compressive sensing to get higher-quality recovered image. The experimental results verify the validity and the reliability of the proposed algorithm.

The “sewing” effect created by the security thread which ‘comes in and out’ of the surface of the paper is obtained thanks to this special process, which transforms the surface of the paper into a delicate transparent veil which covers and highlights the security thread at regular intervals.

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This watermark is produced by ‘flat’ technology machines during the making of paper, the contrasts in the hues are created by the different thicknesses of the fibres in the pulp mixture. As compared to a mould-made watermark, the hue contrasts are less rich and evident, however it still remains one of the most widespread and effective means against counterfeiting of value security paper.

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We included a true in-paper watermark (chain link image) ..

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Visible watermarking is a widely-used technique for marking and protecting copyrights of many millions of images on the web, yet it suffers from an inherent security flaw--watermarks are typically added in a consistent manner to many images. We show that this consistency allows to automatically estimate the watermark and recover the original images with high accuracy. Specifically, we present a generalized multi-image matting algorithm that takes a watermarked image collection as input and automatically estimates the "foreground" (watermark), its alpha matte, and the "background" (original) images. Since such an attack relies on the consistency of watermarks across image collection, we explore and evaluate how it is affected by various types of inconsistencies in the watermark embedding that could potentially be used to make watermarking more secured. We demonstrate the algorithm on stock imagery available on the web, and provide extensive quantitative analysis on synthetic watermarked data. A key takeaway message of this paper is that visible watermarks should be designed to not only be robust against removal from a single image, but to be more resistant to mass-scale removal from image collections as well.

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