An Adjustable Interpolation-based Data Hiding Algorithm Based on LSB Substitution and Histogram Shifting

2016 ◽  
Vol 8 (2) ◽  
pp. 48-61 ◽  
Author(s):  
Yuan-Yu Tsai ◽  
Yao-Hsien Huang ◽  
Ruo-Jhu Lin ◽  
Chi-Shiang Chan
Keyword(s):  
Image Processing ◽  
Data Hiding ◽  
Adjustment Process ◽  
Histogram Shifting ◽  
Embedding Capacity ◽  
Visual Distortion ◽  
Capacity Calculation ◽  
Block Complexity ◽  
Fixed Embedding ◽  
Lsb Substitution

Data hiding can be regarded as a type of image processing techniques. Other image processing operations are usually integrated to increase the embedding capacity or decrease the visual distortion. Interpolation is an example of this type of operation. However, previous interpolation-based data hiding algorithms suffered from low and fixed embedding capacity and high visual distortion. This study proposes a more effective two-stage data hiding algorithm based on interpolation, LSB substitution, and histogram shifting. First, the authors modify the formula for embedding capacity calculation and make some adjustments on the sample pixels determination. A threshold is used to obtain the block complexity and each embeddable pixel has a different amount of message embedded. Second, an LSB substitution method and an optimal pixel adjustment process are adopted to raise the image quality. Finally, the authors' proposed algorithm can support adjustable embedding capacity. Compared to the previous algorithm, the experimental results demonstrate the feasibility of the proposed method.

Steganographic data hiding in image processing using predictive differencing

2012 ◽  
Vol 20 (2) ◽  
Author(s):  
C. Weng ◽  
H. Tso ◽  
S. Wang
Keyword(s):  
Image Processing ◽  
Data Hiding ◽  
Predictive Value ◽  
Experimental Result ◽  
Embedding Capacity ◽  
High Quality ◽  
Pixel Value ◽  
Pixel Value Differencing

AbstractIn this paper, we propose a stenography scheme based on predictive differencing to embed data in a grey-image. In order to promote the embedding capacity of pixel-value differencing (PVD), we use differencing between a predictive value and an input pixel as the predictive differencing to embed the message where a predictive value is calculated by using various predictors. If the predictive differencing is large, then it means that the input pixel is located in the edge area and, thus, has a larger embedding capacity than the pixel in a smooth area. The experimental result shows that our proposed scheme is capable of providing greater embedding capacity and high quality of stego-images then previous works. Furthermore, we have also applied various predictors to evaluate our proposed scheme.

Block-Based Reversible Data Hiding Using Histogram Shifting and Modulus Operator for Digital Images

2017 ◽  
Vol 26 (06) ◽  
pp. 1750103 ◽  
Author(s):  
Pankaj Garg ◽  
Singara Singh Kasana ◽  
Geeta Kasana
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Signal To Noise Ratio ◽  
Cover Image ◽  
Histogram Shifting ◽  
Embedding Capacity ◽  
Signal To Noise ◽  
Secret Data ◽  
Peak Points ◽  
Block Based

A Reversible Data Hiding technique by using histogram shifting and modulus operator is proposed in which secret data is embedded into blocks of the cover image. These blocks are modified by using modulus operator to increase the number of peak points in the histogram of the cover image which further increases its embedding capacity. Secret data is embedded in the original cover blocks of the cover image by using peak points of the predicted blocks, which are generated by using modulus operator. Peak Signal to Noise Ratio and PSNR-Human Visual System are used to show the human visual acceptance of the proposed technique. Experimental results show that the embedding capacity is high as compared to the capacity of existing RDH techniques, while distortion in marked images is also less as compared to distortion produced by these existing techniques.

STEGANOGRAPHIC SCHEME FOR GRAY-LEVEL IMAGE USING PIXEL NEIGHBORHOOD AND LSB SUBSTITUTION

2010 ◽  
Vol 10 (04) ◽  
pp. 589-607 ◽  
Author(s):  
NAGARAJ V. DHARWADKAR ◽  
B. B. AMBERKER
Keyword(s):  
Image Processing ◽  
Secret Message ◽  
Gray Level ◽  
Embedding Capacity ◽  
Least Significant Bit ◽  
Secret Communication ◽  
Gray Level Image ◽  
Pixel Value ◽  
Pixel Value Differencing ◽  
Lsb Substitution

The exchange of secret message using images has vital importance in secret communication. Steganographic scheme is employed to achieve the task of secret message communication using images. The existing scheme based on pixel value differencing (PVD) with least significant bit (LSB) sequential substitution suffer from low embedding capacity. The embedding capacity is increased by using the edge regions of image obtained by neighborhood connectivity of pixel. We propose an adaptive steganographic scheme for gray-level images. Our scheme relies on the neighborhood connectivity of pixels to estimate the embedding capacity and resolves the problem of sequential substitution by jumbling the bits of secret message. The effect of cropping and filtration attacks on stegoimage is minimized by embedding the copies of secret message into four different regions of the cover image. The performance of the scheme is analyzed for various types of image processing attacks like cropping, blurring, filtering, adding noise, and sharpening. The proposed scheme is found rigid to these attacks.

scholarly journals High-Capacity Data Hiding for ABTC-EQ Based Compressed Image

Electronics ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 644 ◽  
Author(s):  
Cheonshik Kim ◽  
Ching-Nung Yang ◽  
Lu Leng
Keyword(s):  
Data Hiding ◽  
High Capacity ◽  
Block Size ◽  
Adjustment Process ◽  
Embedding Capacity ◽  
High Quality Image ◽  
Quality Image ◽  
Capacity Data ◽  
Complex Block

We present a new data hiding method based on Adaptive BTC Edge Quantization (ABTC-EQ) using an optimal pixel adjustment process (OPAP) to optimize two quantization levels. The reason we choose ABTC-EQ as a cover media is that it is superior to AMBTC in maintaining a high-quality image after encoding is executed. ABTC-EQ is represented by a form of t r i o ( Q 1 , Q 2 , [ Q 3 ] , BM) where Q is quantization levels ( Q 1 ≤ Q 2 ≤ Q 3 ) , and BM is a bitmap). The number of quantization levels are two or three, depending on whether the cover image has an edge or not. Before embedding secret bits in every block, we categorize every block into smooth block or complex block by a threshold. In case a block size is 4x4, the sixteen secret bits are replaced by a bitmap of the smooth block for embedding a message directly. On the other hand, OPAP method conceals 1 bit into LSB and 2LSB respectively, and maintains the quality of an image as a way of minimizing the errors which occur in the embedding procedure. The sufficient experimental results demonsrate that the performance of our proposed scheme is satisfactory in terms of the embedding capacity and quality of an image.

scholarly journals Histogram Based Data Cryptographic Technique with High Level Security

2019 ◽  
Vol 8 (04) ◽  
pp. 08-14
Author(s):  
Prof. Romi Morzelona
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Original Image ◽  
Histogram Shifting ◽  
Embedding Capacity ◽  
Bit Rate ◽  
Secret Data ◽  
Additional Information ◽  
High Level ◽  
Embedding Function

Histogram shifting plays a major role in reversible data hiding technique. By this shifting method the distortion is reduced and the embedding capacity may be increased. This proposed work uses, shifting and embedding function. The pixel elements of the original image are divided into two disjoint groups. The first group is used to carry the secret data and the second group adds some additional information which ensures the reversibility of data. The  parameter such as PSNR, embedding capacity and bit rate are used for comparisons of various images

scholarly journals Generalized Reversible Data Hiding with Content-Adaptive Operation and Fast Histogram Shifting Optimization

Entropy ◽  
2021 ◽  
Vol 23 (7) ◽  
pp. 917
Author(s):  
Limengnan Zhou ◽  
Hongyu Han ◽  
Hanzhou Wu
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Hot Spot ◽  
Data Embedding ◽  
Histogram Shifting ◽  
Secret Data ◽  
Content Selection ◽  
Wide Range ◽  
Map Generation ◽  
Content Adaptive

Reversible data hiding (RDH) has become a hot spot in recent years as it allows both the secret data and the raw host to be perfectly reconstructed, which is quite desirable in sensitive applications requiring no degradation of the host. A lot of RDH algorithms have been designed by a sophisticated empirical way. It is not easy to extend them to a general case, which, to a certain extent, may have limited their wide-range applicability. Therefore, it motivates us to revisit the conventional RDH algorithms and present a general framework of RDH in this paper. The proposed framework divides the system design of RDH at the data hider side into four important parts, i.e., binary-map generation, content prediction, content selection, and data embedding, so that the data hider can easily design and implement, as well as improve, an RDH system. For each part, we introduce content-adaptive techniques that can benefit the subsequent data-embedding procedure. We also analyze the relationships between these four parts and present different perspectives. In addition, we introduce a fast histogram shifting optimization (FastHiSO) algorithm for data embedding to keep the payload-distortion performance sufficient while reducing the computational complexity. Two RDH algorithms are presented to show the efficiency and applicability of the proposed framework. It is expected that the proposed framework can benefit the design of an RDH system, and the introduced techniques can be incorporated into the design of advanced RDH algorithms.

scholarly journals Efficient Reversible Data Hiding Scheme for AMBTC-Compressed Images

2021 ◽  
Vol 11 (15) ◽  
pp. 6741
Author(s):  
Chia-Chen Lin ◽  
Thai-Son Nguyen ◽  
Chin-Chen Chang ◽  
Wen-Chi Chang
Keyword(s):  
Data Hiding ◽  
Free Space ◽  
Reversible Data Hiding ◽  
Secret Message ◽  
Embedding Capacity ◽  
Absolute Moment ◽  
Compressed Images ◽  
High Embedding Capacity ◽  
Significant Attention ◽  
Efficiency Rate

Reversible data hiding has attracted significant attention from researchers because it can extract an embedded secret message correctly and recover a cover image without distortion. In this paper, a novel, efficient reversible data hiding scheme is proposed for absolute moment block truncation code (AMBTC) compressed images. The proposed scheme is based on the high correlation of neighboring values in two mean tables of AMBTC-compressed images to further losslessly encode these values and create free space for containing a secret message. Experimental results demonstrated that the proposed scheme obtained a high embedding capacity and guaranteed the same PSNRs as the traditional AMBTC algorithm. In addition, the proposed scheme achieved a higher embedding capacity and higher efficiency rate than those of some previous schemes while maintaining an acceptable bit rate.

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