A blind color image watermarking algorithm combined spatial domain and SVD

Abstract

It has great significance for protecting the image copyright with color image digital watermarking technique, which needs the watermarking algorithm has high robustness, good imperceptibility and short running-time. A blind colour image watermarking algorithm combined spatial domain and singular value decomposition (SVD) is designed to protect the rightful ownership of color image in this paper. The theoretical principle combined SVD and spatial domain is first discussed and proposed in this paper. Based on the derived principle, the watermark information can be directly embedded into the maximum singular value (MSV) of the host image in the spatial domain by the new quantization index modulation with variable quantization step, and the embedded watermark information can be directly extracted from the MSV of the watermarked image block in the spatial domain with geometrical correction. The contributions of this paper include the following four points: (1) the relationship between the changed MSV of SVD and the average changed value of image pixel in the spatial domain is the first derived in this paper; (2) the presented method has the merits of both spatial-domain technique and transform-domain technique; (3) the relationships of each component of the color image are used to improve the invisibility and the geometrical correction of watermarked image is also adapted to further improve the robustness; and (4) this presented method overcomes the

Privacy‐preserving image retrieval in a distributed environment

“…The following experiments only consider some cases where the value of n is small since only a small number of cloud servers are usually deployed in real scenarios considering the consumption of human resources and material resources. k n ( , ) = (2, 3), (2,4), (3,4) are chosen as the test thresholds.…”

“…Hence EI 12 and EI 52 are unvalid and should be filtered out by PS Mean average precision (MAP) is used to quantify the retrieval accuracy. Seven images are randomly selected from each class as query images for Top-K retrievals where K = {1, 2, …, 40} under different k n ( , ) = (2, 3), (2,4), (3,4). The average of the precisions of these retrievals is the mAP value under given α = {0, 0.1, 0.2, 0.3, 0.4, 0.5} (no less than half of pixels in the image are encrypted at group-based WRCA encryption f G to ensure image security) and β = {24, 36, 48, 72, 96}.…”

“…Despite the tremendous benefits, image security and privacy become the most significant concern about cloud computing that must be well-addressed. 2,3 Image encryption [4][5][6] is a mature technology to protect image privacy from leaking in the cloud environment since it can completely hide the information of the original images. However, it impedes further image processing operations such as image retrieval.…”

A watermarking scheme for dual‐color images based on URV decomposition and image correction

“…According to different extraction methods of watermarks, it can be divided into nonblind watermarking 24 and blind watermarking. [25][26][27][28][29][30][31][32][33][34][35][36][37] According to different embedding domains of watermarks, it can be divided into spatial-domain watermarking 27,32,34 and frequency-domain watermarking. 25,26,[28][29][30][31]33,[35][36][37] Because carrier information is difficult to be obtained in practical applications, blind watermarking is more extensive and has higher practical value.…”

“…There are many algorithms used in digital watermarking schemes, such as discrete cosine transform (DCT), 25,26 discrete wavelet transform, 27,28 Schur decomposition, 29,30 eigenvalue decomposition (EVD), 31 singular value decomposition (SVD), 32,33 and other transforms. [34][35][36][37] Yuan et al 25 proposed a DCT-based color image watermarking scheme.…”