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Image hashing is an efficient technique of many multimedia systems, such as image retrieval, image authentication and image copy detection. Classification between robustness and discrimination is one of the most important performances of image hashing. In this paper, we propose a robust image hashing with singular values of quaternion singular value decomposition (QSVD). The key contribution is the innovative use of QSVD, which can extract stable and discriminative image features from CIE L*a*b* color space. In addition, image features of a block are viewed as a point in the Cartesian coordinates and compressed by calculating the Euclidean distance between its point and a reference point. As the Euclidean distance requires smaller storage than the original block features, this technique helps to make a discriminative and compact hash. Experiments with three open image databases are conducted to validate efficiency of our image hashing. The results demonstrate that our image hashing can resist many digital operations and reaches a good discrimination. Receiver operating characteristic curve comparisons illustrate that our image hashing outperforms some state-of-the-art algorithms in classification performance. [ABSTRACT FROM AUTHOR]

Video hashing is a novel technique of multimedia processing and finds applications in video retrieval, video copy detection, anti-piracy search and video authentication. In this paper, we propose a robust video hashing based on discrete cosine transform (DCT) and non-negative matrix decomposition (NMF). The proposed video hashing extracts secure features from a normalized video via random partition and dominant DCT coefficients, and exploits NMF to learn a compact representation from the secure features. Experiments with 2050 videos are carried out to validate efficiency of the proposed video hashing. The results show that the proposed video hashing is robust to many digital operations and reaches good discrimination. Receiver operating characteristic (ROC) curve comparisons illustrate that the proposed video hashing outperforms some state-of-the-art algorithms in classification between robustness and discrimination. [ABSTRACT FROM AUTHOR]

We propose a novel image encryption scheme that utilizes chaotic maps and random scan patterns to protect image content. Our scheme includes three stages: pixel permutation via random scan patterns, block pixel diffusion, and block permutation. In the first stage, the input image is partitioned into overlapping blocks, and random scan patterns controlled by chaotic maps are exploited to scramble pixels of blocks. In the second stage, content-based keys are generated from the input image, and the content-based keys and chaotic maps are used to calculate secure matrices for achieving diffusion. The block pixel diffusion is conducted by performing element-wise XOR operation between blocks and their corresponding secure matrices. In the third stage, the image is partitioned into non-overlapping blocks, and all blocks are randomly permuted to further improve security. Key space analysis shows that the key space of the proposed scheme is bigger than those of some existing schemes. Experiments on standard test images are conducted by using some well-known metrics, such as histogram, χ2 test, correlation coefficient, entropy, the number of pixels change rate, the unified average changing intensity, and peak signal-to-noise ratio. The results demonstrate that the proposed scheme reaches the state-of-the-art performance in security and speed. [ABSTRACT FROM AUTHOR]

A reversible data hiding (RDH) method with prediction error histogram (PEH) decomposition and hybrid dimensional histogram modification is proposed. First, a global one-dimensional (1D) PEH is generated by pixel-based pixel value ordering predictor. The proposed method fully utilizes the pixels inside the range of the minimum and maximum of neighbors to decompose 1D-PEH into several sub 1D-PEHs. Then, each sub 1D-PEH is separated into two parts. The part with small-magnitude is used to construct a reduced two-dimensional (2D) PEH, whereas the rest is shifted for reversibility. Finally, data embedding is performed by modifying each reduced 2D-PEH to reduce distortion. Experimental results demonstrates that the proposed method outperforms some high-fidelity RDH methods. [ABSTRACT FROM AUTHOR]

We investigate the use of parabolic interpolation in data hiding and propose a novel data hiding algorithm with high capacity based on interpolated image. Specifically, the proposed algorithm creates an interpolated image from input image by parabolic interpolation, and embeds secret bits into interpolated pixels in terms of the relation between the interpolated value and the mean value. Ten standard benchmark images are taken as test images for validating efficiency of our algorithm. The results illustrate that our algorithm has better performances than some popular data hiding methods in embedding capacity and visual quality with respect to PSNR and SSIM. [ABSTRACT FROM AUTHOR]