Chuan Qin

Effective reversible data hiding in encrypted image with privacy protection for image content

A novel reversible data hiding scheme in encrypted image is proposed.Data hiding is conducted with elaborate selection for partial pixels to be flipped.Secret bits can be extracted by adaptive smoothness evaluation in isophote direction.Our scheme has better decrypted image quality and higher image recovery accuracy. In this paper, we propose a novel reversible data hiding scheme in encrypted image. The content owner encrypts the original image with the encryption key to achieve privacy protection for image content, and then, each block of the encrypted image is embedded with one secret bit by the data hider using the data-hiding key. Through the elaborate selection for partial pixels to be flipped, data hiding process only conducts slighter modifications to each block, which leads to significant improvement of visual quality for the decrypted image. The receiver can easily decrypt the marked, encrypted image using the encryption key, and then, through the data-hiding key and an adaptive evaluation function of smoothness characteristic along the isophote direction, secret data can be extracted from the decrypted image, and the original image can further be recovered successfully. Experimental results demonstrate the effectiveness of the proposed scheme.

Self-embedding fragile watermarking with restoration capability based on adaptive bit allocation mechanism

In this paper, we propose a novel fragile watermarking scheme with content restoration capability. Authentication-bits are produced using the image hashing method with a folding operation. The low-frequency component of the nonsubsampled contourlet transform (NSCT) coefficients is used to encode the restoration-bits for each block by the adaptive bit allocation mechanism. During the bit allocation, all the blocks are categorized into different types according to their degree of smoothness, and, complex blocks, which are deemed to have higher priority than smooth blocks, are allocated more bits. Two algorithms are utilized to adjust the block classification and the binary representations in order to guarantee that the numbers of the self-embedding authentication-bits and restoration-bits are exactly suitable for 1-LSB embedding capacity. On the receiver side, the extracted authentication-bits and the decoded restoration-bits are used to localize and restore the tampered blocks, respectively. Due to the low embedding volume, the visual quality of the watermarked image is satisfactory. Experimental results also show that the proposed scheme provides high restoration quality.

Efficient reversible data hiding for VQ-compressed images based on index mapping mechanism

In this paper, we propose a novel reversible data-hiding scheme in the index tables of the vector quantization (VQ) compressed images based on index mapping mechanism. On the sender side, the VQ indices with zero occurrence numbers in a given index table of an image are utilized to construct a series of index mappings together with some indices with the largest occurrence numbers. The indices in each constructed mapping correspond to the full binary representations with the length of the mapping bit number. Through the mapping optimization by index histogram, the optimal vector of mapping bit numbers can be obtained, which leads to the highest hiding capacity. Data embedding procedure can be easily achieved by the simple index substitutions according the current subset of secret bits for hiding. The same index mappings reconstructed on the receiver side ensure the correctness of secret data extraction and the lossless recovery of index table. Experimental results demonstrate the effectiveness of the proposed scheme.

Robust image hashing using non-uniform sampling in discrete Fourier domain

This paper proposes a robust image hashing method in discrete Fourier domain that can be applied in such fields as image authentication and retrieval. In the pre-processing stage, image resizing and total variation based filtering are first used to regularize the input image. Then the secondary image is obtained by the rotation projection, and the robust frequency feature is extracted from the secondary image after discrete Fourier transform. More sampling points are chosen from the low- and middle-frequency component to represent the salient content of the image effectively, which is achieved by the non-uniform sampling. Finally, the intermediate sampling feature vectors are scrambled and quantized to produce the resulting binary hash securely. The security of the method depends entirely on the secret key. Experiments are conducted to show that the present method has satisfactory robustness against perceptual content-preserving manipulations and has also very low probability for collision of the hashes of distinct images.

Adaptive self-recovery for tampered images based on VQ indexing and inpainting

In this paper, we propose a novel self-recovery scheme for tampered images using vector quantization (VQ) indexing and image inpainting. Cover image blocks are classified into complex blocks and smooth blocks according to the distribution characteristics. Due to the good performance of the compressed representation of VQ and the automatic repairing capability of image inpainting, the recovery-bits of each cover block are generated by its VQ index and the inpainting indicator. Recovery-bits and authentication-bits are embedded into the LSB planes of the cover image to produce the watermarked image. On the receiver side, after tampered blocks are all localized, the extracted recovery-bits are used to judge the classification of each tampered block. By analyzing the validity of the VQ indices and the damaged degree of the neighboring regions, the adaptive recovery mechanism can be utilized to restore all the tampered blocks by using VQ index and image inpainting. Experimental results demonstrate the effectiveness of the proposed scheme.

Improved dual-image reversible data hiding method using the selection strategy of shiftable pixels' coordinates with minimum distortion

Compared to conventional reversible data hiding (RDH) methods, the dual-image RDH technique is an effective way to achieve greater embedding rate and better quality of the stego images. Motivated by the center folding-based, dual-image RDH method proposed by Lu et al. (SIGNAL PROCESSING, 115 (2015) 195213), we propose an improved dual-image RDH method by using the selection strategy of shiftable pixels coordinates with minimum distortion. Although the stego dual-pixel in the center folding-based method is shifted with minimum distortion, there is another shiftable pixel-coordinate that can be used without creating any extra distortion. Based on this observation, the embedding rate can be improved without any deterioration of visual quality by embedding an extra message bit into each newfound alternative pixel-coordinate. In addition, the range of parameter k, which controls the embedding rate, in our method is extended to greater than or equal to 1, therefore, a higher visual quality can be achieved when k is set at 1. The experimental results showed that the embedding rate of our method is greater than that of the center folding-based method for the same stego image quality, and our method outperforms other methods, whether in term of average PSNR or embedding rate. Explore the potential improvements in center folding based dual-image RDH method.Use the selection strategy of shiftable pixels coordinates with minimum distortion.The parameter in the proposed method is extended to 1 to achieve a lower distortion.

Guided filtering based color image reversible data hiding

An improved color image RDH method is proposed.The inter-channel correlation is exploited throughout the whole process.Guided filtering technique is employed in the procedure of pixel prediction.An adaptive payload partition scheme for RGB channels is proposed. In this paper, a color-image-dedicated reversible data hiding (RDH) algorithm is proposed to improve embedding performance by applying a guided filtering predictor and an adaptive prediction-error expansion (PEE) scheme. PEE-based RDH methods can be mainly separated into two stages for each channel embedding, i.e., pixel prediction and prediction-error histogram (PEH) modification. In our work, the inter-channel correlation is exploited at all stages of prediction and modification. Specifically, for predicting the pixels in the current channel with the guidance of pixels from other channels, a linear transform model from reference channels to the current channel is established and its coefficients are determined by the Laplacian minimization criterion. Then, to modify the PEH, an adaptive PEE embedding scheme is conducted by seeking the optimal parameters of the embedding bins and the complexity threshold to minimize distortion. The experimental results demonstrate the proposed method has better performance than the state-of-the-art, color-image RDH methods.

Robust image hashing with embedding vector variance of LLE

We investigate the use of LLE in image hashing.We find that embedding vector variances of LLE are approximately linearly changed by content-preserving operations.We propose a robust image hashing based on this LLE property.Our hashing outperforms some notable algorithms in classification performances. Locally linear embedding (LLE) has been widely used in data processing, such as data clustering, video identification and face recognition, but its application in image hashing is still limited. In this work, we investigate the use of LLE in image hashing and find that embedding vector variances of LLE are approximately linearly changed by content-preserving operations. Based on this observation, we propose a novel LLE-based image hashing. Specifically, an input image is firstly mapped to a normalized matrix by bilinear interpolation, color space conversion, block mean extraction, and Gaussian low-pass filtering. The normalized matrix is then exploited to construct a secondary image. Finally, LLE is applied to the secondary image and the embedding vector variances of LLE are used to form image hash. Hash similarity is determined by correlation coefficient. Many experiments are conducted to validate our efficiency and the results illustrate that our hashing is robust to content-preserving operations and reaches a good discrimination. Comparisons of receiver operating characteristics (ROC) curve indicate that our hashing outperforms some notable hashing algorithms in classification between robustness and discrimination.

Fragile Watermarking with Self-recovery Capability via Absolute Moment Block Truncation Coding

In this paper, we propose a fragile image watermarking scheme based on Absolute Moment Block Truncation Coding (AMBTC) and self-embedding. According to the constructed binary map and two reconstruction levels, each non-overlapping block in original image can be compressed with the AMBTC algorithm. Then, after scrambling, the compression codes are extended through a random matrix, which can introduce more redundancy into the reference bits to be embedded for content recovery. Also, the relationship between each image block and each reference bit is built so that the recoverable area for tampered image can be increased. Experimental results demonstrate the effectiveness of the proposed scheme.

Detection of Double-Compressed H.264/AVC Video Incorporating the Features of the String of Data Bits and Skip Macroblocks

Today’s H.264/AVC coded videos have a high quality, high data-compression ratio. They also have a strong fault tolerance, better network adaptability, and have been widely applied on the Internet. With the popularity of powerful and easy-to-use video editing software, digital videos can be tampered with in various ways. Therefore, the double compression in the H.264/AVC video can be used as a first step in the study of video-tampering forensics. This paper proposes a simple, but effective, double-compression detection method that analyzes the periodic features of the string of data bits (SODBs) and the skip macroblocks (S-MBs) for all I-frames and P-frames in a double-compressed H.264/AVC video. For a given suspicious video, the SODBs and S-MBs are extracted for each frame. Both features are then incorporated to generate one enhanced feature to represent the periodic artifact of the double-compressed video. Finally, a time-domain analysis is conducted to detect the periodicity of the features. The primary Group of Pictures (GOP) size is estimated based on an exhaustive strategy. The experimental results demonstrate the efficacy of the proposed method.