Xiangui Kang

A DWT-DFT composite watermarking scheme robust to both affine transform and JPEG compression

Robustness is a crucially important issue in watermarking. Robustness against geometric distortion and JPEG compression at the same time with blind extraction remains especially challenging. A blind discrete wavelet transform-discrete Fourier transform (DWT-DFT) composite image watermarking algorithm that is robust against both affine transformation and JPEG compression is proposed. The algorithm improves robustness by using a new embedding strategy, watermark structure, 2D interleaving, and synchronization technique. A spread-spectrum-based informative watermark with a training sequence is embedded in the coefficients of the LL subband in the DWT domain while a template is embedded in the middle frequency components in the DFT domain. In watermark extraction, we first detect the template in a possibly corrupted watermarked image to obtain the parameters of an affine transform and convert the image back to its original shape. Then, we perform translation registration using the training sequence embedded in the DWT domain, and, finally, extract the informative watermark. Experimental work demonstrates that the proposed algorithm generates a more robust watermark than other reported watermarking algorithms. Specifically it is robust simultaneously against almost all affine transform related testing functions in StirMark 3.1 and JPEG compression with quality factor as low as 10. While the approach is presented for gray-level images, it can also be applied to color images and video sequences.

Enhancing Source Camera Identification Performance With a Camera Reference Phase Sensor Pattern Noise

Sensor pattern noise (SPN) extracted from digital images has been proved to be a unique fingerprint of digital cameras. However, SPN can be contaminated largely in the frequency domain by image content and nonunique artefacts of JPEG compression, on-sensor signal transfer, sensor design, color interpolation. The source camera identification (CI) performance based on SPN needs to be improved for small sizes of images and especially in resisting JPEG compression. Because the SPN is modelled as an additive white Gaussian noise (AWGN) in its extraction process from an image, it is reasonable to assume the camera reference SPN to be a white noise signal in order to remove the interference mentioned above. The noise residues (SPN) extracted from the original images are whitened first, then they are averaged to generate the camera reference SPN. Motivated by Goljan s test statistic peak to correlation energy (PCE), we propose to use correlation to circular correlation norm (CCN) as the test statistic, which can lower the false positive rate to be a half of that with PCE. Theoretical analysis shows that the proposed CI method can remove the interference and raise the CCN value of a positive sample and thus achieve greater CI performance, CCN values of the negative sample class with the proposed method follow the normal distribution N (0,1) and the false positive rate can be calculated. Compared with the existing state of the art on seven cameras, 1400 photos totally (200 for each camera), the experimental results show that the proposed CI method achieves the best receiver operating characteristic (ROC) performance among all CI methods in all cases and especially achieves much better resistance to JPEG compression than all of the existing state-of-the-art CI methods.

Geometric Invariant Audio Watermarking Based on an LCM Feature

The development of a geometric invariant audio watermarking scheme without degrading acoustical quality is challenging work. This paper proposes a multi-bit spread-spectrum audio watermarking scheme based on a geometric invariant log coordinate mapping (LCM) feature. The LCM feature is very robust to audio geometric distortions. The watermark is embedded in the LCM feature, but it is actually embedded in the Fourier coefficients which are mapped to the feature via LCM, so the embedding is actually performed in the DFT domain without interpolation, thus eliminating completely the severe distortion resulted from the non-uniform interpolation mapping. The watermarked audio achieves high auditory quality in both objective and subjective quality assessments. A mixed correlation between the LCM feature and a key-generated PN tracking sequence is proposed to align the log-coordinate mapping, thus synchronizing the watermark efficiently with only one FFT and one IFFT. Both the theoretical analysis and experimental results show that the proposed audio watermarking scheme is not only resilient against common signal processing operations, including low-pass filtering, MP3 recompression, echo addition, volume change, normalization, test functions in the Stirmark benchmark, and DA/AD conversion, but also has conquered the challenging audio geometric distortion and achieves the best robustness against simultaneous geometric distortions, such as pitch invariant time-scale modification (TSM) by ±20%, tempo invariant pitch shifting by 20%, resample TSM with scaling factors between 75% and 140%, and random cropping by 95%. This is mainly contributed by the proposed geometric invariant LCM feature. To our best knowledge, audio watermarking based on LCM has not been reported before.

Efficient General Print-Scanning Resilient Data Hiding Based on Uniform Log-Polar Mapping

This paper proposes an efficient, blind, and robust data hiding scheme which is resilient to both geometric distortion and the general print-scan process, based on a near uniform log-polar mapping (ULPM). In contrast to performing inverse log-polar mapping (a mapping from the log-polar system to the Cartesian system) to the watermark signal or its index as done in the prior works, we apply ULPM to the frequency index (u, v) in the Cartesian system to obtain the discrete log-polar coordinate (l 1, l 2), then embed one watermark bit w(l 1 ,l 2 ) in the corresponding discrete Fourier transform coefficient c(u,v). This mapping of index from the Cartesian system to the log-polar system but embedding the corresponding watermark directly in the Cartesian domain not only completely removes the interpolation distortion and the interference distortion introduced to the watermark signal as observed in some prior works, but also largely expands the cardinality of watermark in the log-polar mapping domain. Both theoretical analysis and experimental results show that the proposed watermarking scheme achieves excellent robustness to geometric distortion, normal signal processing, and the general print-scan process. Compared to existing watermarking schemes, our algorithm offers significant improvement in terms of robustness against general print-scan, receiver operating characteristic (ROC) performance, and efficiency of blind resynchronization.

Improving Robustness of Quantization-Based Image Watermarking via Adaptive Receiver

In this paper, the watermarking channel is modeled as a generalized channel with fading and nonzero mean additive noise. In order to improve the watermark robustness against the generalized channel, we present an optimized watermark extraction scheme by using an adaptive receiver for quantization-based watermarking. In the proposed extraction scheme, we adaptively estimate the decision zone of the binary data bits and the quantization step size. A training sequence is embedded into the original image together with the informative watermark. The estimation of the decision zone takes advantage of the response function of the training sequence. Compared to those watermarking schemes without receiver adaptation, the main improvement is the enhanced robustness against median filtering, image intensity Direct Current (DC) change, histogram equalization, color reduction, image intensity linear scaling, image intensity nonlinear scaling such as Gamma correction etc.

A context adaptive predictor of sensor pattern noise for camera source identification

Sensor pattern noise (SPN) is a noise-like spread-spectrum signal inherently cast onto every digital image by each imaging device and has been recognised as a reliable device fingerprint for camera source identification (CSI) and image origin verification. It can be estimated as the noise residual between the image content and its denoised version. However, the SPN extracted from a single image can be contaminated largely by image scene because image edge noise is usually much stronger than the SPN. So the identification performance is heavily dependent upon the purity of the estimated SPN, especially for small size images because they have less and weaker SPN. Although there are some existing works dedicated to improving the performance of source camera identification, an effective method to eliminate the contamination of image scene and extract an accurate SPN is currently lacking. In this paper, we will propose an edge adaptive SPN predictor based on context adaptive interpolation (PCAI) to exclude the contamination of image scene. Different from most of the existing methods extracting SPN from wavelet high frequency coefficients, we extract SPN directly from the spatial domain with a pixel-wise adaptive Wiener filter, based on the assumption that the SPN is a white signal. Extensive experiments show that our proposed PCAI method achieves the best receiver operating characteristic (ROC) performance among all of the state-of-the-art CSI schemes on different sizes of images, and has the best performance in resisting JPEG compression (e.g. with a quality factor of 90%) simultaneously.

An image watermarking algorithm robust to geometric distortion

Digital image watermark is an invisible mark embedded in an image that can be used for copyright protection. The current paper proposes a new watermarking scheme by improving image normalization based watermarking (INW). Image normalization is based on the moments of the image, however, in general, RST attacks bring the image boundary cropping and the moments are not preserved original ones. Thereafter the normalized images of before and after are not same form. To solve the cropping problem of INW, Invariant Centroid (IC) is proposed and the only central region(R), which has less cropping possibility by RST, is used for normalization. In addition, the watermark is embedded and detected in the normalized form of the image. Experimental results demonstrated that the proposed watermarking scheme is robust to RST attacks with cropping.

Robust Audio Watermarking Based on Log-Polar Frequency Index

In this paper, we analyze the audio signal distortions introduced by pitch-scaling, random cropping and DA/AD conversion, and find a robust feature, average Fourier magnitude over the log-polar frequency index(AFM), which can resist these attacks. Theoretical analysis and extensive experiments demonstrate that AFM is an appropriate embedding region for robust audio watermarking. This is the first work on applying log-polar mapping to audio watermark. The usage of log-polar mapping in our work is basically different from the existing works in image watermarking. The log-polar mapping is only applied to the frequency index, not to the transform coefficients, which avoids the reconstruction distortion of inverse log-polar transform and reduces the computation cost. Comparison with the existing methods, the proposed AFM-based watermarking scheme has the outstanding performance on resisting pitch-scaling and random cropping, as well as very approving robustness to DA/AD conversion and TSM (Time-Scale Modification). The watermarked audio achieves high auditory quality. Experimental results show that the scheme is very robust to common audio signal processing and distortions introduced in Stirmark for Audio.

Mixed-strategy Nash equilibrium in the camera source identification game

Although sensor pattern noise (SPN) is recognized as a reliable device fingerprint for camera source identification (CSI), this fingerprint could have been forged by anti-forensics. In order to evaluate the performance in the case of both forensic investigator and forger exist, we model this interplay as a camera source identification game. The mixed-strategy Nash equilibrium is introduced to solve this game. The Nash equilibrium receiver operating characteristic (ROC) curves are obtained experimentally. Through our analysis, we are able to determine under which case the CSI result is reliable.

An efficient print-scanning resilient data hiding scheme based on a novel LPM

Print-scan resilient data hiding has not been extensively researched. This paper presents an efficient multi-bit blind watermarking scheme based on a novel Fourier log-polar mapping (LPM). The watermark resynchronization after print-scanning is efficiently solved by an embedded tracking pattern which cannot be removed by template removing attacks and is not detectable for a malicious part. Experimental results show that the proposed watermarking scheme has excellent robustness to print-scanning, cropping, geometric distortion and JPEG compression etc. The obtained success ratios of extraction 60 bits message without error from the combination attack of JPEG compressed with quality factor of 50-100 and then print- scanning were at least 95%.