An optimal high capacity reversible data hiding scheme using move to front coding for LZW codes

Reversible Data hiding techniques reduce transmission cost as secret data is embedded into a cover image without increasing its size in such a way that at the receiving end, both secret data and the cover image can be extracted and recovered, respectively, to their original form. To further reduce the transmission cost, the secret data can be embedded in the compression codes by some popular reversible data hiding schemes. One of the popular and important reversible data hiding method is high- performance data-hiding Lempel–Ziv–Welch (HPDH-LZW) scheme which hides the secret data in LZW codes. In this paper, the HPDH-LZW scheme is modified in order to increase its hiding capacity and compression ratio. First, the proposed work modifies the Move to Front (MTF) encoding technique to hide the secret data and also to increase the similarity among the element of the cover media. Then, LZW encoding technique is applied on the resultant cover data to obtain LZW codes, which are used to hide further secret data. Experimental results show that the proposed scheme has significantly increased the data hiding capacity and have good embedding and extraction speed in comparison to other state of the art schemes.

     

Extended squared magic matrix for embedding secret information with large payload

Data hiding is a technology designed for safely transmitting secret data through open communication channels, in which the secret data are embedded into a cover carrier imperceptibly. Among the existing data hiding schemes, the exploiting-modification-direction (EMD) based schemes draw considerable attentions due to large embedding capacity. The proposed scheme improves the EMD-2 scheme by constructing an extended squared magic matrix, resulting in a larger embedding capacity high up to 3.15 bits per pixel (bpp). Experimental results show that the proposed scheme outperforms state-of-the-art reference matrix based schemes in terms of embedding capacity, meanwhile, maintains good image quality.

     

FPGA implementation of reversible watermarking in digital images using reversible contrast mapping

Reversible contrast mapping (RCM) and its various modified versions are used extensively in reversible watermarking (RW) to embed secret information into the digital contents. RCM based RW accomplishes a simple integer transform applied on pair of pixels and their least significant bits (LSB) are used for data embedding. It is perfectly invertible even if the LSBs of the transformed pixels are lost during data embedding. RCM offers high embedding rate at relatively low visual distortion (embedding distortion). Moreover, low computation cost and ease of hardware realization make it attractive for real-time implementation. To this aim, this paper proposes a field programmable gate array (FPGA) based very large scale integration (VLSI) architecture of RCM-RW algorithm for digital images that can serve the purpose of media authentication in real-time environment. Two architectures, one for block size (8 × 8) and the other one for (32 × 32) block are developed. The proposed architecture allows a 6-stage pipelining technique to speed up the circuit operation. For a cover image of block size (32 × 32), the proposed architecture requires 9881 slices, 9347 slice flip-flops, 11291 number 4-input LUTs, 3 BRAMs and a data rate of 1.0395 Mbps at an operating frequency as high as 98.76 MHz.     

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 steganographic method for color and grayscale image hiding

In this paper, we present a steganographic method for embedding a color or a grayscale image in a true color image. Three types of secret images can be carried by the proposed method: hiding a color secret image, hiding a palette-based 256-color secret image, and hiding a grayscale image in a true color image. Secret data are protected by the conventional crypto system DES. We compare the image quality and hiding capacity of the proposed method with those of the scheme in Lin et al.’s scheme. According to the experimental results, the image quality of the proposed method is better than that of the Lin et al.’s scheme. In addition, annotation data can be hidden with the secret image in the host image. The hiding capacity of the proposed method is greater than that of other compared schemes. The experimental results show that the proposed method is a secure steganographic method that provides high hiding capacity and good image quality.     

A high capacity data hiding scheme for binary images based on block patterns

This paper proposes a high capacity data hiding scheme for binary images based on block patterns, which can facilitate the authentication and annotation of scanned images. The scheme proposes block patterns for a 2 × 2 block to enforce specific block-based relationship in order to embed a significant amount of data without causing noticeable artifacts. In addition, two kinds of matching pair (MP) methods, internal adjustment MP and external adjustment MP, are designed to decrease the embedding changes. Shuffling is applied before embedding to reduce the distortion and improve the security. Experimental results show that the proposed scheme gives a significantly improved embedding capacity than previous approaches in the same level of embedding distortion. We also analyze the perceptual impact and discuss the robustness and security issues.     

Adaptive lossless steganographic scheme with centralized difference expansion

In this paper, a novel adaptive lossless data hiding scheme is presented that is capable of offering greater embedding capacity than the existing schemes. Unlike the fixed hiding capacity each block provides in most of the currently available lossless data hiding approaches, the proposed method utilizes a block-based lossless data embedding algorithm where the quantity of the hidden information each block bears is variable. To both reduce the image distortion and increase the hiding capacity, the payload of each block depends on its cover image complexity. Due to the fact that schemes with difference expansion tend to damage the image quality seriously in the edge areas, in the proposed scheme, smoother areas are chosen to conceal more secret bits. This way, a better balance can be reached between the embedding ratio and the stego-image quality. In addition, when recovered the cover image can came back to its old self to the last bit without any distortion at all. Experimental results, as this paper will show, have demonstrated that the proposed method is capable of hiding more secret data while maintaining imperceptible stego-image quality degradation.     

High-capacity reversible data hiding method using block expansion in digital images

A reversible data hiding method allows recovery of the cover image after the secret data have been extracted. In this paper, a novel reversible data hiding method is proposed using neighboring interpolation and pixel-value differencing on block expansion. A consecutive embedding technique for a sub-block is proposed to maintain a higher embedding capacity, and a neighboring pixel-value referencing is also proposed to maintain a good visual quality in stego-images. The results of experiment demonstrate that the proposed method has higher capacity and maintains a better image quality than previous reversible data hiding methods.     

Quadruple Difference Expansion-Based Reversible Data Hiding Method for Digital Images

ABSTRACT

Lossless data hiding is a special type of data hiding technique that guarantees not only the secret data but also the ability of cover media to be reconstructed without any distortion. A latest lossless data hiding technique is proposed by Hong Lin Jin's that is based on hiding only one data bit in the spatial domain in gray-level image. However, this method uses double difference expansion to embed bits which results in a small embedding capacity. For this purpose, we propose an improved algorithm with the potential of increasing the payload capacity and maintaining good image quality. The proposed improved algorithm is characterized by two aspects. First, the proposed improved reversible data hiding scheme is enhanced to exhibit data hiding in color palette images. Second, the embedding level is improved by using quadruple difference expansion to guarantee the embedding of 2-bit data into color images. Experiments of the proposed improved method have been conducted over several well-known test images. The results show that the proposed improved method significantly improves the embedding capacity over Hong Lin Jin's scheme by the range of 15–35% for grayscale images and 20–46% for color images while still maintaining the quality of the stego-images.     

A DNA-based data hiding technique with low modification rates

In 2010, Shiu et al. proposed three DNA-based reversible data hiding schemes with high embedding capacity. However, their schemes were not focused on DNA modification rate or the expansion problem. Therefore, we propose a novel reversible data hiding scheme based on histogram technique to solve the weaknesses of Shiu et al.’s schemes. The proposed scheme transforms the DNA sequence into a binary string and then combines several bits into a decimal integer. These decimal integers are used to generate a histogram. Afterwards, the proposed scheme uses a histogram technique to embed secret data. The experimental results show that the modification rate of our proposed scheme is 69 % lower than that of Shiu et al.’s schemes for the same embedding capacity. In addition, the length of the DNA sequence remains unchanged in the proposed scheme.     

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.     

Adjustable prediction-based reversible data hiding

Reversible data hiding has received considerable interest recently in the field of information hiding. However, most of difference expansion (DE-based) schemes suffer from the problem that image cannot be restored into its original one free from location map. Reversible data hiding scheme with location map cannot effectively raise hiding capacity; in addition, it also incurs the computational cost during embedding and extracting. This study presents a reversible data hiding scheme that is free of location map and thus the computational cost, associated with embedding and extracting, is lower than that of most DE-based schemes. Furthermore, our scheme solves the problem of the low embedding rate of Tseng and Hsieh?s scheme because our scheme takes advantage of the bulk of relatively high small prediction-errors to raise embedding capacity. Experimental results demonstrate that the proposed scheme achieves the larger payload and the better image quality than some existing schemes by an adjustable control factor. The performance of the proposed scheme is more stable for the different images.     

An adaptive reversible data hiding scheme based on prediction error histogram shifting by exploiting signed-digit representation

A prediction error histogram shifting (PEHS)-based reversible data hiding scheme is proposed in this paper. A novel representation for the secret stream, called signed-digit representation, is proposed to improve the image quality. The secret binary stream is first converted into a signed-digit stream, which results in a high occurrence of ‘0’. Meanwhile, a block-wise-based prediction is performed on the original image to generate prediction errors, which lead to a sharp prediction error histogram. Then, the converted signed-digit stream is embedded into the prediction errors according to the improved histogram shifting (HS)-based scheme with multiple selected peak points, resulting in an adaptive embedding capacity. The experimental results validate that the proposed scheme outperforms state-of-the-art schemes in terms of embedding capacity while maintaining a good image quality.

     

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.     

Data hiding based on overlapped pixels using hamming code

Most data hiding schemes change the least significant bits to conceal messages in the cover images. Matrix encoding scheme is a well known scheme in this field. The matrix encoding proposed by Crandall can be used in steganographic data hiding methods. Hamming codes are kinds of cover codes. “Hamming + 1” proposed by Zhang et al. is an improved version of matrix encoding steganography. The embedding efficiency of “Hamming + 1” is very high for data hiding, but the embedding rate is low. Our proposed “Hamming + 3” scheme has a slightly reduced embedding efficiency, but improve the embedding rate and image quality. “Hamming + 3” is applied to overlapped blocks, which are composed of 2^k+3 pixels, where k=3. We therefore propose verifying the embedding rate during the embedding and extracting phases. Experimental results show that the reconstructed secret messages are the same as the original secret message, and the proposed scheme exhibits a good embedding rate compared to those of previous schemes.     

Using quad smoothness to efficiently control capacity-distortion of reversible data hiding

One of the main uses of data hiding is to protect secret messages being transmitted on the Internet. Reversible data hiding can fully recover the original host image after extracting the secret message. It is especially suitable for applications where, after extracting the secret message, the quality of the recovered host image cannot be compromised, such as for medical or military image data.Many difference-expansion-based (DE-based) reversible data hiding methods have made use of a threshold value to control the stego-image's quality. Usually repeated trial and error is required to find a relatively good threshold with acceptable capacity-distortion behavior. This paper introduces a scheme that does not require a threshold value, such as is used in Alattar's quad-based reversible data hiding. It applies a prediction of quad of quads smoothness to determine the embedding sequence. The proposed scheme is shown to perform better than other DE-based schemes. Results showed that it has the ability of maintaining embedding quality at all capacity levels, especially when the embedding capacity is at low to medium levels.     

Separable reversible data hiding in encrypted images based on scalable blocks

This paper proposes a new separable reversible data hiding method for encrypted images. Proposed scheme employs the pixel redundancy of natural images to construct embedding space. First, cover image is divided into multiple blocks with different scales. According to the pixel average value of each block, the lowest two bits of every pixel are vacated as reserved rooms. Subsequently, the whole image is encrypted by using stream cipher and the secret messages are finally embedded into the reserved rooms by the embedding key. Proposed scheme is separable in the sense that the recipient can achieve different function by the following ways: (a) If the recipient has only decryption key, an approximation plaintext image containing the embedded information can be obtained. (b) If the recipient has only embedded key, secret messages can be extracted correctly. (c) If the recipient has both decryption key and embedded key, he can not only extract the secret messages, but recover the original cover image perfectly. Extensive experiments are performed to show that our proposed schemes outperform existing reversible data hiding schemes in terms of visual quality, embedding capacity and security performance, even if a large-scale image database is used.

     

Adaptive data hiding for vector quantization images based on overlapping codeword clustering

In this paper, an overlapping codeword clustering based data hiding scheme is presented. In this scheme, a mapping table is designed to determine the overlapping codeword clustering and to indicate the index modification in the secret embedding. The mapping table explores the relationship among the sub-codebook’s size, the codeword’s order and the embedding secret message to which the codeword overlapping in sub-codebooks with different sizes is permitted. In addition, the secret embedding is also determined according to the mapping table.The experimental results showed that the number of partitioned sub-codebooks was increased significantly. The average hiding capacity was about 30 K bits while the average embedding distortion was about 1.2 dB. In comparison to similar methods, the proposed scheme provided a larger hiding capacity than others while preserving a similar stego-image quality. Furthermore, the proposed scheme offered a better proportion of hiding compared to image distortion.     

Hiding data in dual images based on turtle shell matrix with high embedding capacity and reversibility

Reversible data hiding (RDH) is a technology that embeds secret data into a carrier where both the secret data and the carrier can be recovered without any data loss. Inspired by dual images technology, this article proposes to employ a high capacity RDH scheme that is based on turtle shell (TS). We start by constructing a newly designed TS-based reference matrix. Then, two meaningful shadows will be generated after hiding the secret data in the cover image with the reference matrix’s help. Meanwhile, the location conflict problem is solved. On the decoder side, when both shadows are gathered, the data extraction and image recovery can be accomplished using the orientation relationship between two stego pixels that are located at the same coordinates in the two shadows and the reference matrix. Moreover, we introduce a security enhancement technology that improves the security of data extraction. The experiment shows that compared with other state-of-the-art RDH schemes, a higher embedding capacity is achieved by this method, and a good visual quality is retained. Simultaneously, the proposed scheme is effective against attacks on pixel value difference histograms (PDH) and regular singular (RS) analysis.

     

Bivariate quality control using two-stage intelligent monitoring scheme

In manufacturing industries, it is well known that process variation is a major source of poor quality products. As such, monitoring and diagnosis of variation is essential towards continuous quality improvement. This becomes more challenging when involving two correlated variables (bivariate), whereby selection of statistical process control (SPC) scheme becomes more critical. Nevertheless, the existing traditional SPC schemes for bivariate quality control (BQC) were mainly designed for rapid detection of unnatural variation with limited capability in avoiding false alarm, that is, imbalanced monitoring performance. Another issue is the difficulty in identifying the source of unnatural variation, that is, lack of diagnosis, especially when dealing with small shifts. In this research, a scheme to address balanced monitoring and accurate diagnosis was investigated. Design consideration involved extensive simulation experiments to select input representation based on raw data and statistical features, artificial neural network recognizer design based on synergistic model, and monitoring–diagnosis approach based on two-stage technique. The study focused on bivariate process for cross correlation function, ρ = 0.1–0.9 and mean shifts, μ = ±0.75–3.00 standard deviations. The proposed two-stage intelligent monitoring scheme (2S-IMS) gave superior performance, namely, average run length, ARL₁ = 3.18–16.75 (for out-of-control process), ARL₀ = 335.01–543.93 (for in-control process) and recognition accuracy, RA = 89.5–98.5%. This scheme was validated in manufacturing of audio video device component. This research has provided a new perspective in realizing balanced monitoring and accurate diagnosis in BQC.