Development of a data hiding scheme based on combination theory for lowering the visual noise in binary images

In order to raise the embedding capacity and simultaneously reduce the artifact effect caused by embedding secret messages into binary images, a novel data hiding method based on the combination theory is proposed. In the proposed scheme, a secret position matrix is designed to improve the hiding capacity which is capable of preventing the least distortion based on the combination theory. Our new scheme enables users to conceal more than one bit of secret data by changing at most one pixel in one subimage. We have derived a formula for computing the payload and the possible modification pixels of a block. Compared with the existing schemes in terms of the hiding capacity and the visual artifacts, as our experimental results show, the proposed scheme is capable of providing a better image quality protector even with a more efficient secret data hider.     

A reversible data hiding scheme using complementary embedding strategy

Obtaining good visual quality and high hiding capacity with reversible data hiding systems is a technically challenging problem. In this paper, we propose a simple reversible data hiding scheme that uses a complementary hiding strategy. The proposed method embeds one secret bit horizontally and vertically into one cover pixel of a grayscale cover image by decreasing odd-valued pixels and increasing even-valued pixels by one. Experimental results show that the hiding capacity measured by bit per pixel (bpp) of the proposed scheme is at least 1.21 bpp with a PSNR (peak signal-to-noise ratio) value greater than 52 dB for all standard test images. Especially in the case of four-layer embedding, the PSNR value of the proposed method is still greater than 51 dB at a hiding capacity of about 5 bpp for all standard test images. In addition, the proposed method is quite simple because it primarily uses additions and subtractions. These results indicate that the proposed scheme is superior to many existing reversible data hiding schemes introduced in the literature.     

High capacity data hiding schemes for medical images based on difference expansion

Since the difference expansion (DE) technique was proposed, many researchers tried to, improve its performance in terms of hiding capacity and visual quality. In this paper, a new scheme, based on DE is proposed in order to increase the hiding capacity for medical images. One of the characteristics of medical images, among the other types of images, is the large smooth regions. Taking advantage of this characteristic, our scheme divides the image into two regions; smooth region and non-smooth region. For the smooth region, a high embedding capacity scheme is applied, while the original DE method is applied to the non-smooth region. Sixteen DICOM images of different modalities were used for testing the proposed schemes. The results showed that the proposed scheme has higher hiding capacity compared to the original schemes.     

A novel data hiding scheme based on modulus function

Four criteria are generally used to evaluate the performance of data hiding scheme: the embedding capacity, the visual quality of the stego-image, the security, and the complexity of the data-embedding algorithm. However, data hiding schemes seldom take all these factors into consideration. This paper proposes a novel data hiding scheme that uses a simple modulus function to address all the performance criteria listed above. According to the input secret keys, the encoder and decoder use the same set-generation functions H_r() and H_c() to first generate two sets Kr and Kc. A variant Cartesian product is then created using Kr and Kc. Each cover pixel then forms a pixel group with its neighboring pixels by exploiting an efficient modulus function; the secret data are then embedded or extracted via a mapping process between the variant of the Cartesian product and each pixel group. The proposed scheme offers several advantages, namely (1) the embedding capacity can be scaled, (2) a good visual quality of the stego-image can be achieved, (3) the computational cost of embedding or extracting the secret data is low and requires little memory space, (4) secret keys are used to protect the secret data and (5) the problem of overflow or underflow does not occur, regardless of the nature of the cover pixels.We tested the performance of the proposed scheme by comparing it with Mielikainen’s and Zhang and Wang’s schemes for gray-scale images. The experimental results showed that our proposed scheme outperforms Mielikainen’s in three respects, namely scalable embedding capacity, embedding rate, and level of security. Our data hiding scheme also achieved a higher embedding capacity than Zhang and Wang’s. The proposed scheme can easily be applied to both gray-scale and color images. Analyses of its performance showed that our proposed scheme outperforms Tsai and Wang’s in terms of its time complexity and memory space requirement.     

A new data hiding scheme for binary image authentication with small image distortion

A new data hiding scheme for binary image authentication that has a small distortion of the cover image is proposed in this paper. Using the data-embedding algorithm that is based on Hamming codes, the proposed scheme embeds authentication information into the cover image with flipping only a small number of pixels. A special type of the pixels are selected and flipped by a new algorithm to minimize visual distortion. This new algorithm is based on ELSSM (Edge Line Segment Similarity Measure). Randomly shuffling the bit-order of the authentication information to be embedded, the information can only be extracted by the designated receiver who has the symmetric key. We employ two measurement metrics: miss detection rates for the degree of security and PSNR (Peak Signal-to-Noise Ratio) and ELSSM for the degree of the image distortion to demonstrate the feasibility of the proposed scheme. Using these metrics, we analyze the proposed scheme and the previous schemes. The analysis reveals that the proposed scheme requires less image distortion than the previous schemes whilst achieving the same level of the miss detection rate. Experimental results demonstrate that the proposed scheme is more resilient against recent steganalysis attacks than the previous schemes.     

Reversible data hiding exploiting spatial correlation between sub-sampled images

Reversible data hiding enables host media to be restored from marked media without any loss of host information. Since this reversibility helps to make right decision during image analysis, it is highly desired in quality-sensitive imagery where even the minimal distortion introduced by embedding data is unacceptable. In this paper, we propose a reversible data hiding method that modifies the difference histogram between sub-sampled images. It exploits the high spatial correlation inherent in neighboring pixels to achieve high capacity and imperceptible embedding. On various test images including 16-bit images, we demonstrate the validity of our proposed method by comparing to other existing reversible data hiding algorithms. Experimental results support that our method provides high embedding capacity while keeping the distortions at a low level.     

A lossless robust data hiding scheme

This paper presents a lossless robust data hiding scheme. The original cover image can be recovered without any distortion after the hidden data have been extracted if the stego-image remains intact, and on the other hand, the hidden data can still be extracted correctly if the stego-image goes through JPEG compression to some extent. The proposed scheme divides a cover image into a number of non-overlapping blocks and calculates the arithmetic difference of each block. Bits are embedded into blocks by shifting the arithmetic difference values. The shift quantity and shifting rule are fixed for all blocks, and reversibility is achieved. Furthermore, owing to the separation of bit-0-zone and bit-1-zone as well as the particularity of arithmetic difference, minor alteration applying to the stego-image generated by non-malicious attacks such as JPEG compression will not cause the bit-0-zone and the bit-1-zone to overlap, and robustness is achieved. Experimental results show that, compared with previous works, the performance of the proposed scheme is significantly improved.     

Multilevel reversible data hiding based on histogram modification of difference images

Reversible data hiding has drawn considerable attention in recent years. Reversibility allows original media to be completely recovered from marked media without distortion after embedded message has been extracted. In this paper we propose a multilevel reversible data hiding scheme based on the difference image histogram modification that uses the peak point to hide messages. Through a joint imperceptibility and hiding capacity evaluation, we show that our proposed scheme uses a multilevel hiding strategy to achieve large hiding capacity and keep distortion low. Performance comparisons with other existing reversible hiding schemes are provided to demonstrate the validity of our proposed scheme.     

基于分存的多幅图像信息隐藏方案*

在秘密图像分存的基础上,提出一种多幅图像进行信息隐藏的算法。首先把秘密图像分存到指定的两个毫无关系的图像中,然后在公开图像的奇数行（列）嵌入第一幅图像,在偶数行（列）嵌入第二幅图像,从而实现多幅图像在一幅公开图像中的隐藏。给出了两幅图像嵌入一幅图像的实验,并对隐藏性能作了分析与比较。该算法原理简单有效,编程容易,信息的嵌入与提取速度快,并且这种多幅图像进行信息隐藏的方法可以嵌套于目前的大多数算法,有很强的推广性。     

A reversible data hiding scheme based on graph neighbourhood degree

Abstract

The perceptibility and capacity are two vital criteria of data hiding scheme. Concerning these criteria, data hiding algorithm used images as cover object based on the graph theory is proposed in this study. Images are quantised according to determined range and then quantised images are divided into n × n sized blocks. Each block is accepted as a graph and vertexes which have the same quantisation value are accepted as neighbours. Neighbourhood degrees of vertexes are calculated and indices of vertexes that have a neighbourhood degree over the threshold value are stored in the codebook. Pixel values indicated by these indices in the codebook are used for data hiding process. In this algorithm, there is no need for edge extraction because of hiding data to pixels containing vertexes having high neighbourhood degrees. The proposed method is compared with similar methods in literature in terms of the perceptibility and capacity. More successful results are provided than the others.     

Lossless data hiding in JPEG bitstream

This paper proposes a method of embedding secret data into JPEG bitstream by Huffman code mapping. Although JPEG defined 162 different variable length code (VLC) for AC coefficients, many codes are not used during image compression. According to the statistical results of VLC usage in a cover, we map the unused codes to used codes. The relationships of code mapping are performed by modifying the Huffman values defined in the file header. During data hiding, we replace the codes appearing in bitstream by the mapped codes according to the secret bits. The proposed embedding method preserves the image with no quality distortion and provides more embedding capacity.     

增强图像平滑度的可逆信息隐藏方案

随着互联网技术的发展和社交网络的普及,可逆信息隐藏技术因其具有无损恢复载体信息的特性而被广泛应用于医疗、军事等领域的隐蔽信息传输。传统的可逆信息隐藏方案大多聚焦于嵌入容量提升和载密图像失真率降低,并未过多关注人们对图像视觉细节的要求,难以抵抗隐藏信息检测方法。针对上述挑战,从增强图像视觉平滑度方面入手,提出了一种增强图像平滑度的可逆信息隐藏方案,在嵌入隐蔽信息的同时提升载密图像最终的视觉质量。具体来说,所提方案将目标图像分为参考区域与非参考区域,利用非参考区域的图像像素预测值与原始像素值的差值作为信息嵌入的判断依据,通过差值平移来嵌入信息;进而构造图像平滑机制,采用高斯滤波作为秘密信息嵌入时像素值修改的模板,对预测值进行滤波计算,将滤波差值无损地加入载体图像中,以达到图像平滑的效果;同时将参考区域的像素值作为边信息,用于实现信息提取方对原始载体图像和秘密信息的无损恢复和提取;并以高斯函数中的滤波系数作为预置秘密信息对嵌入信息进行加密处理以保证嵌入信息的机密性。大量经典图像数据集的测试与分析结果表明,所提方案处理过的载密图像视觉平滑度得到了显著增强,具有较低的失真率、较高的嵌入率和较高的嵌入提取效率。在典型环境下,其生成的载密图像与高斯滤波后的图像相似度可达0.996 3,且可获得37.346的峰值信噪比和0.328 9的嵌入容量。     

Hiding data in compressive sensed measurements: A conditionally reversible data hiding scheme for compressively sensed measurements

Most of the real-world signals we encounter in real-life applications have low information content. In other words, these signals can be well approximated by sparse signals in a proper basis. Compressive sensing framework uses this fact and attempts to represent signals by using far fewer measurements as compared to conventional acquisition systems. While the CS acquisition is linear, the reconstruction of the signal from its sparse samples is nonlinear and complex. The sparse nature of the signal allows enough room for some additional data sequence to be inserted and exactly recovered along with the reconstructed signal. In this study, we propose to linearly embed and hide data in compressively sensed signals and nonlinearly reconstruct both of them using a deflationary approach. We investigate the embedding capacity as a function of signal sparsity and signal compression, as well as the noise sensitivity of the proposed algorithm.     

一个新的基于多重秘密共享的图像隐藏方案

提出了一种新的图像隐藏方案,该方案糅合了多重秘密共享思想与LSB算法,生成的影子图像约为秘密图像的1/t,从而减小了载体图像的容量。本方案允许任意选取 (t-1)次多项式的模数p,并根据该模数p将秘密图像的若干个像素点拼接成一个数据单元,有效克服了Thien方案中秘密图像需进行置乱处理的缺陷。此外,本方案构造的多项式明显少于Thien方案和Li Bai方案。     

An adaptive data hiding scheme with high embedding capacity and visual image quality based on SMVQ prediction through classification codebooks

This study exploits the characteristics of image blocks to develop an adaptive data hiding scheme that is based on SMVQ prediction. Since human beings’ eyes are highly sensitive to smooth images, changes in smooth cause great distortion and attract the attention of interceptors. Hence, this study proposes a data embedding scheme for embedding secret data into edge blocks and non-sufficiently smooth blocks. The experimental results show that the proposed scheme improves the quality of the stego-image and the embedding capacity.     

A high capacity reversible data hiding scheme with edge prediction and difference expansion

To enhance the embedding capacity of a reversible data hiding system, in this paper, a novel multiple-base lossless scheme based on JPEG-LS pixel value prediction and reversible difference expansion will be presented. The proposed scheme employs a pixel value prediction mechanism to decrease the distortion caused by the hiding of the secret data. In general, the prediction error value tends to be much smaller in smooth areas than in edge areas, and more secret data embedded in smooth areas still meets better stego-image quality. The multiple-base notational system, on the other hand, is applied to increase the payload of the image. With the system, the payload of each pixel, determined by the complexity of its neighboring pixels, can be very different. In addition, the cover image processed by the proposed scheme can be fully recovered without any distortion. Experimental results, as shown in this paper, have demonstrated that the proposed method is capable of hiding more secret data while keeping the stego-image quality degradation imperceptible.     

A ROI-based high capacity reversible data hiding scheme with contrast enhancement for medical images

Multimedia Tools and Applications - In this paper, we attempt to investigate the secure archiving of medical images which are stored on semi-trusted cloud servers, and focus on addressing the...