A new data encoding based on maximum to minimum histogram in reversible data hiding

The dual stego images based on data hiding has become popular in recent days. Since the embedding rate in dual stego images is very high. This paper proposes a new data encoding method based on maximum to the minimum histogram in reversible data hiding. This method estimates the encoded intensity from the message intensity and embeds the encoded intensity in the cover image. The stego image quality decreases the intensity of the hidden data which is high. The intensity of the data must be kept low to maintain a high-quality stego image. It is achieved using data encoding. Therefore, the proposed method uses new data encoding which converts the higher histogram data to lower intensity and the lower histogram data to higher intensity during the data embedding process. In the extraction process, the encoded intensities are decoded to message intensities to obtain the original data. The proposed data hiding approach has improved in terms of image quality (PSNR), structure similarity index measurements and embedding rate.     

Binary Image Steganalysis Based on Distortion Level Co-Occurrence Matrix

In recent years, binary image steganography has developed so rapidly that the research of binary image steganalysis becomes more important for information security. In most state-of-the-art binary image steganographic schemes, they always find out the flippable pixels to minimize the embedding distortions. For this reason, the stego images generated by the previous schemes maintain visual quality and it is hard for steganalyzer to capture the embedding trace in spacial domain. However, the distortion maps can be calculated for cover and stego images and the difference between them is significant. In this paper, a novel binary image steganalytic scheme is proposed, which is based on distortion level co-occurrence matrix. The proposed scheme first generates the corresponding distortion maps for cover and stego images. Then the co-occurrence matrix is constructed on the distortion level maps to represent the features of cover and stego images. Finally, support vector machine, based on the gaussian kernel, is used to classify the features. Compared with the prior steganalytic methods, experimental results demonstrate that the proposed scheme can effectively detect stego images.     

Digital color image watermarking based on phase-shifting interferometry and neighboring pixel value subtraction algorithm in the discrete-cosine-transform domain

A novel single-channel color-image watermarking with digital-optics means based on phase-shifting interferometry (PSI) and a neighboring pixel value subtraction algorithm in the discrete-cosine-transform (DCT) domain is proposed. The converted two-dimensional indexed image matrix from an original color image is encrypted to four interferograms by a PSI and double random-phase encoding technique. Then the interferograms are embedded in one chosen channel of an enlarged color host image in the DCT domain. The hidden color image can be retrieved by DCT, the improved neighboring pixel value subtraction algorithm, an inverse encryption process, and color image format conversion. The feasibility of this method and its robustness against some types of distortion and attacks from the superposed image with different weighting factors are verified and analyzed by computer simulations. This approach can avoid the cross-talk noise due to direct information superposition, enhance the imperceptibility of hidden data, and improve the efficiency of data transmission.     

Optical watermark scheme based on singular value decomposition ghost imaging and particle swarm optimization algorithm

An optical image watermarking algorithm, based on singular value decomposition (SVD) ghost imaging and multiple transforms, is designed. The watermark image is first encrypted by applying an SVD ghost imaging system, then the encrypted watermark is embedded into the cover image with the help of multiple transforms, including lifting wavelet transform (LWT), discrete cosine transform (DCT), discrete fractional angular transform (DFAT) and SVD. Four sub-band images are produced from the host image by LWT and DCT. The improved DFAT, whose scaling factors and parameter are optimized by particle swarm optimization algorithm, is operated in the new matrix. Afterwards, SVD is executed in the two-part image and the encrypted watermark is embedded in the host image by mutual operation of different matrices. Simulation results validate that the proposed watermark scheme is superior in the aspects of security, robustness and imperceptibility.     

A Triple-Channel Encrypted Hybrid Fusion Technique to Improve Security of Medical Images

Assuring medical images protection and robustness is a compulsory necessity nowadays. In this paper, a novel technique is proposed that fuses the wavelet-induced multi-resolution decomposition of the Discrete Wavelet Transform (DWT) with the energy compaction of the Discrete Wavelet Transform (DCT). The multi-level Encryption-based Hybrid Fusion Technique (EbhFT) aims to achieve great advances in terms of imperceptibility and security of medical images. A DWT disintegrated sub-band of a cover image is reformed simultaneously using the DCT transform. Afterwards, a 64-bit hex key is employed to encrypt the host image as well as participate in the second key creation process to encode the watermark. Lastly, a PN-sequence key is formed along with a supplementary key in the third layer of the EbHFT. Thus, the watermarked image is generated by enclosing both keys into DWT and DCT coefficients. The fusions ability of the proposed EbHFT technique makes the best use of the distinct privileges of using both DWT and DCT methods. In order to validate the proposed technique, a standard dataset of medical images is used. Simulation results show higher performance of the visual quality (i.e., 57.65) for the watermarked forms of all types of medical images. In addition, EbHFT robustness outperforms an existing scheme tested for the same dataset in terms of Normalized Correlation (NC). Finally, extra protection for digital images from against illegal replicating and unapproved tampering using the proposed technique.     

Reversible Data Hiding in Encrypted Images Based on Prediction and Adaptive Classification Scrambling

Reversible data hiding in encrypted images (RDH-EI) technology is widely used in cloud storage for image privacy protection. In order to improve the embedding capacity of the RDH-EI algorithm and the security of the encrypted images, we proposed a reversible data hiding algorithm for encrypted images based on prediction and adaptive classification scrambling. First, the prediction error image is obtained by a novel prediction method before encryption. Then, the image pixel values are divided into two categories by the threshold range, which is selected adaptively according to the image content. Multiple high-significant bits of pixels within the threshold range are used for embedding data and pixel values outside the threshold range remain unchanged. The optimal threshold selected adaptively ensures the maximum embedding capacity of the algorithm. Moreover, the security of encrypted images can be improved by the combination of XOR encryption and classification scrambling encryption since the embedded data is independent of the pixel position. Experiment results demonstrate that the proposed method has higher embedding capacity compared with the current state-ofthe-art methods for images with different texture complexity.     

A Novel Robust Watermarking Algorithm for Encrypted Medical Image Based on DTCWT-DCT and Chaotic Map

In order to solve the problem of patient information security protection in medical images, whilst also taking into consideration the unchangeable particularity of medical images to the lesion area and the need for medical images themselves to be protected, a novel robust watermarking algorithm for encrypted medical images based on dual-tree complex wavelet transform and discrete cosine transform (DTCWT-DCT) and chaotic map is proposed in this paper. First, DTCWT-DCT transformation was performed on medical images, and dot product was per-formed in relation to the transformation matrix and logistic map. Inverse transformation was undertaken to obtain encrypted medical images. Then, in the low-frequency part of the DTCWT-DCT transformation coefficient of the encrypted medical image, a set of 32 bits visual feature vectors that can effectively resist geometric attacks are found to be the feature vector of the encrypted medical image by using perceptual hashing. After that, different logistic initial values and growth parameters were set to encrypt the watermark, and zero-watermark technology was used to embed and extract the encrypted medical images by combining cryptography and third-party concepts. The proposed watermarking algorithm does not change the region of interest of medical images thus it does not affect the judgment of doctors. Additionally, the security of the algorithm is enhanced by using chaotic mapping, which is sensitive to the initial value in order to encrypt the medical image and the watermark. The simulation results show that the pro-posed algorithm has good homomorphism, which can not only protect the original medical image and the watermark information, but can also embed and extract the watermark directly in the encrypted image, eliminating the potential risk of decrypting the embedded watermark and extracting watermark. Compared with the recent related research, the proposed algorithm solves the contradiction between robustness and invisibility of the watermarking algorithm for encrypted medical images, and it has good results against both conventional attacks and geometric attacks. Under geometric attacks in particular, the proposed algorithm performs much better than existing algorithms.     

Data hiding based on generalised exploiting modification direction method

Abstract

Two schemes using the exploiting modification direction (EMD) method to obtain good stego image quality and increase embedding capacity were respectfully introduced by Zhang and Wang and Lee et al. This study proposes a data-hiding scheme based on an improved EMD method. According to experimental results, the proposed scheme retains high embedding capacity and good stego image quality.     

基于YCoCg-R颜色空间与离散余弦变换的自适应彩色图像水印算法

目的为了解决当前彩色图像水印技术的水印容量和不可感知性不佳等问题,设计基于YC_oC_g-R颜色空间和离散余弦变换的自适应图像水印算法。方法首先,将载体图像从RGB空间转换到YC_oC_g-R空间,计算Y,C_o,C_g这3个颜色分量;随后,引入离散余弦变换DCT对Y分量进行处理,获取相应的DCT系数;引入模糊聚类分析,将DCT低频系数视为局部特征,利用SVM机制对DCT低频系数进行训练分类,确定出适合嵌入水印的DCT系数;设计水印嵌入机制,将水印数据隐藏到合适的DCT低频系数中;借助可逆DCT方法,将Y分量从频域变换到空域;联合初始的C_o与C_g分量,将其变换到RGB空间,输出水印图像;最后,通过相应的水印提取方法,复原初始水印信息。结果测试数据表明,与当前水印方法相比,所提技术具有更高的不可感知性与水印容量,其水印图像的PSNR值为43.67 dB,且其允许的水印容量可超过1 bits,在多种攻击下,复原水印的质量更高,相关系数NC均超过了0.92。结论所提技术能够较好地将水印信息隐藏在载体图像中,具有较高的鲁棒性和安全性。     

USAD: undetectable steganographic approach in DCT domain

In this work, we propose a new adaptive chaotic steganographic method based on the Discrete Cosine Transform (DCT) and a reversible mapping function. The mapping function is used to map the secret bits into their corresponding symbols. This mapping technique has to preserve the same dynamics, properties and distribution of the original DCT coefficients. The novelty of our approach is based on the adaptive selection phase of embedding spots. This selection is established through a blindness condition which is applied over each image of the database. The proposed embedding scheme within the middle DCT coefficients shows lower probability of detection and higher flexibility in extraction. We evaluate the detection of our method using the Ensemble Classifiers and a set of frequency and spatial domain feature extractors such as the Spatial domain Rich Model (SRM) features, Chen et al.'s 486-dimensional both inter- and intra-block Markov-based features and Liu's 216-dimensional adaptive steganography-based features.     

New LSB-based colour image steganography method to enhance the efficiency in payload capacity,security and integrity check

Steganography is the technique for hiding information within a carrier file so that it is imperceptible for unauthorized parties. In this study, it is intended to combine many techniques to gather a new method for colour image steganography to obtain enhanced efficiency, attain increased payload capacity, posses integrity check and security with cryptography at the same time. Proposed work supports many different formats as payload. In the proposed method, the codeword is firstly formed with secret data and its CRC-32 checksum, then the codeword is compressed by Gzip just before encrypting it by AES, and it is finally added to encrypted header information for further process and then embedded into the cover image. Embedding the encrypted data and header information process utilizes Fisher-Yates Shuffle algorithm for selecting next pixel location. To hide one byte, different LSB (least significant bits) of all colour channels of the selected pixel is exploited. In order to evaluate the proposed method, comparative performance tests are carried out against different spatial image steganographic techniques using some of the well-known image quality metrics. For security analysis, histogram, enhanced LSB and Chi-square analyses are carried out. The results indicate that with the proposed method has an improved payload capacity, security and integrity check for common problems of simple LSB method. Moreover, it has been shown that the proposed method increases the visual quality of the stego image when compared to other studied methods, and makes the secret message difficult to be discovered.     

基于图像特征区域的加密全息水印算法

针对图像的特征区域,提出了一种变换域的加密全息水印算法。根据K-均值聚类思想,将图像分为前、后景区特征区域,用双随机相位调制为全息水印加密,提高水印的安全性;通过DCT 变换,在变换域中将加密的全息水印嵌入中频系数,兼顾了人眼的视觉特性和水印的鲁棒性,且属于盲水印算法。实验结果表明,该水印算法能够抵抗常见的各种攻击,重建水印清晰、有效,水印具有极强的隐蔽性、鲁棒性和安全性。     

基于视觉内容分析和遗传算法优化的鲁棒图像水印算法

目的为了兼顾水印图像的不可感知性与鲁棒性,利用DCT(Discrete Cosine Transform)变换域,设计载体视觉内容分析耦合遗传算法优化的鲁棒图像水印技术。方法首先,将载体图像分割为一系列的非重叠子块,并引入奇异值分解机制,定义视觉内容分析方法,获取每个子块的活性因子,活性因子值较大的子块为水印嵌入位置;利用DCT机制处理活性因子值较大的子块得到相应的直流系数;联合结构相似度SSIM、峰值信噪比PSNR以及归一化相关系数NC,并基于权重因子设计适应度函数,通过执行遗传算法寻找最优的嵌入强度;根据优化的嵌入强度构建水印嵌入方法,将二值水印隐藏到这些直流系数中,通过逆DCT变换输出水印图像;设计水印检测方法,从水印图像中提取二值水印。结果实验数据显示,与当前基于变换域的水印技术相比,所提算法具有更高的视觉不可感知性与抗几何攻击能力,面对多种几何攻击,所提算法的PSNR与NC值分别保持在45 dB,0.96以上。结论所提算法能够较好地将水印信息隐藏在载体中,具有较高的视觉不可感知性与抗几何攻击能力,在版权保护、信息防伪等领域具有较好的参考价值。     

Reversible Data Hiding in Classification-Scrambling Encrypted-Image Based on Iterative Recovery

To improve the security and quality of decrypted images, this work proposes a reversible data hiding in encrypted image based on iterative recovery. The encrypted image is firstly generated by the pixel classification scrambling and bit-wise exclusive-OR (XOR), which improves the security of encrypted images. And then, a pixel-type-mark generation method based on block-compression is designed to reduce the extra burden of key management and transfer. At last, an iterative recovery strategy is proposed to optimize the marked decrypted image, which allows the original image to be obtained only using the encryption key. The proposed reversible data hiding scheme in encrypted image is not vulnerable to the ciphertext-only attack due to the fact that the XOR-encrypted pixels are scrambled in the corresponding encrypted image. Experimental results demonstrate that the decrypted images obtained by the proposed method are the same as the original ones, and the maximum embedding rate of proposed method is higher than the previously reported reversible data hiding methods in encrypted image.     

一种基于混沌映射的鲁棒性图形水印算法

提出了一种基于混沌映射的DCT域数字图像水印算法。将含有特定信息的二值序列作为原始水印,利用混沌密码对其进行加密,并在嵌入时再利用混沌映射将水印信息嵌入原始图像的DCT域,使得水印方案具有双重安全性。由于在水印检测时不需要原始图像的参与,该算法实现了水印的盲检测。实验结果表明,用该算法嵌入的水印信息具有不可见性,其对常见的图像处理如JPEG压缩、噪声、滤波以及剪切等具有良好的鲁棒性。     

The new block pixel sort algorithm for TVC-encrypted medical image

To transfer the medical image from one place to another place or to store a medical image in a particular place with secure manner has become a challenge. In order to solve those problems, the medical image is encrypting and compressing before sending or saving at a place. In this paper, a new block pixel sort algorithm has been proposed for compressing the encrypted medical image. The encrypted medical image acts as an input for this compression process. During the compression, encrypted secret image E₁₂(;) is compressed by the pixel block sort encoding (PBSE). The image is divided into four identical blocks, similar to 2×2 matrix. The minimum occurrence pixel(s) are found out from every block and the positions of the minimum occurrence pixel(s) are found using the verdict occurrence process. The pixel positions are shortened with the help of a shortening process. The features (symbols and shortened pixel positions) are extracted from each block and the extracted features are stored in a particular place, and the values of these features put together as a compressed medical image. The next process of PBSE is pixel block short decoding (PBSD) process. In the decoding process, there are nine steps involved while decompressing the compressed encrypted medical image. The feature extraction value of compressed information is found out from the feature extraction, the symbols are split and the positions are shortened in a separate manner. The position is retrieved from the rescheduled process and the symbols and reconstructed positions of the minimum occurrence pixels are taken block wise. Every symbol is placed based on the position in each block: if the minimum occurrence pixel is ‘0’, then the rest of the places are automatically allocated as ‘1’ or if the minimum occurrence pixel is ‘1’ the remaining place is automatically allocated as ‘0’. Both the blocks are merged as per order 2×2. The final output is the reconstructed encrypted medical image. From this compression method, we can achieve the high compression ratio, minimum time, less compression size and lossless compression, which are the things experimented and proved.     

Rotation-invariant fingerprint matching using radon and DCT

A new set of promising rotation-invariant features based on radon and discrete cosine transform (DCT) is proposed for fingerprint matching. The radon and DCT of a tiny area in the region of core point of fingerprint image is computed. In the proposed method only 34% DCT coefficients are used for feature extraction. Competency of this approach is tested on standard databases, namely FVC2002 and FVC2004. This approach provides 70% genuine acceptance rate (GAR) at ~0% false acceptance rate (FAR) and 95% GAR at 10% FAR on rotated and non-rotated databases, respectively. Experimental results prove that the proposed feature extraction approach is rotation invariant.     

一种小波和余弦变换组合域内鲁棒的自适应零水印算法

克服了传统数字水印方案在嵌入水印时要对原始图像数据进行一定修改从而导致嵌入水印图像质量下降的局限性,提出了一个基于离散小波变换和离散余弦变换组合域内鲁棒的自适应零水印算法.算法首先对原始数字图像进行适当层次的离散小波变换,并对得到的小波逼近子图进行离散余弦变换,然后依据待嵌入二值字符水印的大小和相应的系数差值要求自适应...     

Bone microarchitecture characterization based on fractal analysis in spatial frequency domain imaging

This paper suggests a new technique for trabecular bone characterization using fractal analysis of X‐Ray and MRI texture images for osteoporosis diagnosis. Osteoporosis is a chronic disease characterized by a decrease in bone density that can lead to fracture and disability. In essence, the proposed fractal model makes use of the differential box‐counting method (DBCM) to estimate the fractal dimension (FD) after an appropriate image preprocessing stage that ensures a robust estimation process. In this study, we showed that within the frequency domain generated through discrete cosine transform (DCT), only a quarter of DCT coefficients are enough to characterize osteoporotic tissues. The algorithmic complexity of the developed approach is of the order of where N stands for the size of the image, which, in turn, likely yields important gain in terms of medication cost. We report a successful separation of healthy and pathological cases in term of both P ? value (using statistical Wilcoxon rank sum test) and margin difference. A comparative statistical analysis has been performed using a publicly available database that contains a set of MRI and X‐Ray texture images of both healthy and osteoporotic bone tissues. The statistical results demonstrated the feasibility and accepted performance level of our fractal model‐based diagnosis to discriminate healthy and unhealthy trabecular bone tissues. The developed approach has been implemented on a medical device prototype.