Digital watermarking has been proposed as an effective technology of copyright protection and content authentication, yet up to now, research on the robust watermarking against geometric attacks is still a challenging task. This paper presents a novel robust watermarking algorithm in nonsubsampled shearlet transform (NSST) domain using quaternion polar harmonic transform (PHT) and least squares support vector regression (LS-SVR), which is a recently developed geometric correction algorithm for digital color image. The major innovative works of the proposed approach lie in that (1) the NSST is applied to embed the watermark, which can provide the image function with nearly optimal approximation and employ fully the properties of human visual system (HVS), (2) the robust 2D transform, namely quaternion PHT is introduced to represent the characteristics of color image, and (3) the novel synchronous correction method is proposed using the excellent LS-SVR and quaternion PHTs, which can accurately estimate the geometric distortions parameters. In our experiments, we applied the proposed method to the standard color image test dataset, and the experimental results demonstrate that the proposed algorithm is not only invisible, but also robustness against common signal processing operations and geometric attacks.

Moments and moment invariants have become a powerful tool in image processing owing to their image description capability and invariance property. But, conventional methods are mainly introduced to deal with the binary or gray-scale images, and the only approaches for color image always have poor color image description capability. Based on Exponent moments (EMs) and quaternion, we introduced the quaternion Exponent moments (QEMs) for describing color images in this paper, which can be seen as the generalization of EMs for gray-level images. It is shown that the QEMs can be obtained from the EMs of each color channel. We derived and analyzed the rotation, scaling, and translation (RST) invariant property of QEMs. We also discussed the problem of color image retrieval using QEMs. Experimental results are provided to illustrate the efficiency of the proposed color image descriptors.

It is a challenging work to design a robust color image watermarking scheme against geometric distortions. Moments and moment invariants have become a powerful tool in robust image watermarking owing to their image description capability and geometric invariance property. However, the existing moment-based watermarking schemes were mainly designed for gray images but not for color images, and detection quality and robustness will be lowered when watermark is directly embedded into the luminance component or three color channels of color images. Furthermore, the imperceptibility of the embedded watermark is not well guaranteed. Based on algebra of quaternions and polar harmonic transform (PHT), we introduced the quaternion polar harmonic transform (QPHT) for invariant color image watermarking in this article, which can be seen as the generalization of PHT for gray-level images. It is shown that the QPHT can be obtained from the PHT of each color channel. We derived and analyzed the rotation, scaling, and translation (RST) invariant property of QPHT. We also discussed the problem of color image watermarking using QPHT. Experimental results are provided to illustrate the efficiency of the proposed color image watermarking against geometric distortions and common image processing operations (including color attacks).

Geometric distortions that cause displacement between embedding and detection are usually difficult for watermark to survive. It is a challenging work to design a robust image watermarking scheme against geometric distortions, especially for local geometric distortions. Based on probability density and complex angular radial transform theory, a new image watermarking algorithm robust to geometric distortions is proposed in this paper. We firstly extract the steady image feature points by using new image feature point detector, which is based on the probability density. Then we build the affine invariant local feature regions based on probability density auto-correlation matrix. And finally, we present a new image watermarking algorithm robust to geometric distortions, in which the digital watermark is embedded into the local complex angular radial transform (CART) coefficients. Experiments results show that the proposed image watermarking is not only invisible and robust against common image processing operations, but also robust against the geometric distortions.

One of the challenges in the development of a content-based image indexing and retrieval application is to achieve an efficient and robust indexing scheme. Color is a fundamental image feature used in content-based image retrieval (CBIR) systems. This paper proposes a robust and effective image retrieval scheme, which is based on the weighed color histogram of visual attention points. Firstly, the fully affine invariant visual attention points are extracted from the origin color image by using the Affine-SIFT (scale-invariant feature transform) detector. Secondly, according to the color complexity measure (CCM) theory, the visual weight values for the significant visual attention points are calculated to reflect the image local variation. Then, the weighed color histogram of visual attention points is constructed. Finally, the similarity between color images is computed by using the weighed color histogram of visual attention points. Experimental results show that the proposed image retrieval is not only more accurate and efficient in retrieving the user-interested images, but also yields higher retrieval accuracy than some state-of-the-art image retrieval schemes for various test DBs.

The development of a desynchronization invariant audio watermarking scheme without degrading acoustical quality is a challenging work. This paper proposes a robust audio watermarking scheme in Empirical Mode Decomposition (EMD) domain, in which the higher-order statistics and synchronization code are utilized. Firstly, the wavelet de-noising is performed on the original host audio, the de-noised digital audio is segmented, and then each segment is cut into two parts. Secondly, with the spatial watermarking technique, synchronization code is embedded into the statistics average value of audio samples in the first part. Thirdly, for the second part, EMD is performed, and a series of Intrinsic Mode Functions (IMFs) and a residual are given, and then the higher-order statistics of residual are obtained by using the Hausdorff distance. Finally, the digital watermark is embedded into the residual in EMD domain by using the higher-order statistics. Simulation results show that the proposed watermarking scheme is not only inaudible and robust against common signal processing operations such as MP3 compression, noise addition,resampling, and re-quantization etc, but also robust against the desynchronization attacks such as random cropping, amplitude variation, pitch shifting, and jittering etc.

Robust digital watermarking has been an active research topic in the last decade. As one of the promising approaches, feature point based image watermarking has attracted many researchers. However, the related work usually suffers from the following limitations: 1) The feature point detector is sensitive to texture region, and some noise feature points are always detected in the texture region. 2) The feature points focus too much on high contrast region, and the feature points are distributed unevenly. Based on Bayesian image segmentation, we propose a local geometrically invariant image watermarking scheme with good visual quality in this paper. Firstly, the Bayesian image segmentation is used to segment the host image into several homogeneous regions. Secondly, for each homogeneous region, image feature points are extracted using the multiscale Harris-Laplace detector, and the corresponding invariant local image regions are constructed adaptively. Finally, by taking the human visual system (HVS) into account, digital watermark is repeatedly embedded into local image regions by modulating the magnitudes of DFT coefficients. By binding the digital watermark with the invariant local image regions, 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 etc, but also robust against the geometric distortions.

In this paper, a new ROI based color image retrieval is proposed. Firstly, the ROI are extracted in DWT domain by using the human visual characteristic and K-mean clustering. Secondly, the ROI is segmented into subregions, and the ROI features are extracted from the subregions (the dominant color and its percentage is used for color feature, the pixel distribution in the subregion is used for shape feature). Finally, the average similarity between images is computed according to the ROI above features. Experimental results show that our image retrieval is more accurate and efficient in retrieving the user-interested images when there are ROI in the image (especially for the image with simple background).