scholarly journals A Steganographic Method with an Overlapping of Three Pixel Block of Image

2020 ◽  
Vol 9 (4) ◽  
pp. 1427-1431
Keyword(s):  
Visual Quality ◽  
The Other ◽  
Embedding Capacity ◽  
Secret Data ◽  
Stego Image ◽  
Hiding Capacity ◽  
Pixel Value ◽  
The Common ◽  
Pixel Value Differencing

In this paper a new image steganographic technique has been proposed which is capable of hiding data and produces a stego image that is totally indistinguishable from the original image by the human eye. To estimate the contrast and smoothness of pixels we check the relation between neighboring pixels. Our method first arranges the pixel in ascending manner, then takes the highest pixel value common with the other two pixels and then applies the pixel value differencing (PVD) method. To hide the secret data PVD technique is used in each pixel block. The two overlapping blocks are readjusted to attain the modified three-pixel components. Then calculate the new stego pixel block. In this way, take the middle and lowest pixel as the common pixel and apply the same procedure. In comparison, we get that if the highest value pixel value takes as a common one then the data hiding capacity is increased. The embedding capacity of the cover image is increased by using the pixel block overlapping mechanism. It has been tested on a set of images and also maintains the visual quality of the image.

Efficient Pixel-Value Differencing Based Hybrid Steganographic Method Using Modulus Function

2020 ◽  
Vol 10 (4) ◽  
pp. 51-62
Author(s):  
Aruna Malik ◽  
Sonal Gandhi
Keyword(s):  
The Other ◽  
Modulus Function ◽  
Second Phase ◽  
Embedding Capacity ◽  
Secret Data ◽  
Stego Image ◽  
Pixel Value ◽  
High Embedding Capacity ◽  
Two Phases ◽  
Pixel Value Differencing

In the era of cloud computing and Big Data, steganographic methods are playing a pivotal role to provide security to sensitive contents. In the steganographic domain, pixel-value differencing (PVD) proposed by Wu and Tsai has been one of the most researched and popular methods as the PVD technique provides good quality stego-image along with high embedding capacity. This article extends the Wu and Tsai's work by proposing a new hybrid steganography scheme which works in two phases to increase the embedding capacity along with stego-image quality. In the first phase, the cover image is preprocessed using a segmentation table to make the image more robust for PVD method. In the second phase, the resultant image is partitioned into 2×1 pixels size blocks in a non-overlapping fashion and then modulus function based scheme is applied in reversible manner. Thus, a significant amount of secret data is embedded into the image. The experimental results prove that the proposed scheme has significantly improved in embedding capacity and quality as compared to the other related PVD-based methods.

scholarly journals An RGB colour image steganography scheme using overlapping block-based pixel-value differencing

2017 ◽  
Vol 4 (4) ◽  
pp. 161066 ◽  
Author(s):  
Shiv Prasad ◽  
Arup Kumar Pal
Keyword(s):  
Cover Image ◽  
Secret Message ◽  
Embedding Capacity ◽  
Secret Data ◽  
Stego Image ◽  
Colour Image ◽  
Pixel Value ◽  
Block Based ◽  
Pixel Value Differencing

This paper presents a steganographic scheme based on the RGB colour cover image. The secret message bits are embedded into each colour pixel sequentially by the pixel-value differencing (PVD) technique. PVD basically works on two consecutive non-overlapping components; as a result, the straightforward conventional PVD technique is not applicable to embed the secret message bits into a colour pixel, since a colour pixel consists of three colour components, i.e. red, green and blue. Hence, in the proposed scheme, initially the three colour components are represented into two overlapping blocks like the combination of red and green colour components, while another one is the combination of green and blue colour components, respectively. Later, the PVD technique is employed on each block independently to embed the secret data. The two overlapping blocks are readjusted to attain the modified three colour components. The notion of overlapping blocks has improved the embedding capacity of the cover image. The scheme has been tested on a set of colour images and satisfactory results have been achieved in terms of embedding capacity and upholding the acceptable visual quality of the stego-image.

scholarly journals High-Capacity Image Steganography with Minimum Modified Bits Based on Data Mapping and LSB Substitution

2018 ◽  
Vol 8 (11) ◽  
pp. 2199 ◽  
Author(s):  
Abdul Zakaria ◽  
Mehdi Hussain ◽  
Ainuddin Wahab ◽  
Mohd Idris ◽  
Norli Abdullah ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
High Capacity ◽  
Visual Quality ◽  
Data Mapping ◽  
Embedding Capacity ◽  
Secret Data ◽  
Stego Image ◽  
Mapping Strategy ◽  
Lsb Substitution

Steganography is the art and practice of communication using hidden messages. The least significant bits (LSB) based method is the well-known type of steganography in the spatial domain. Usually, achieving the larger embedding capacity in LSB-based methods requires a large number of LSB bits modification which indirectly reduces the visual quality of stego-image and increases the risk of steganalysis detection attacks. In this study, we propose a novel steganography method with data mapping strategy which can reduce the number of bits modification per pixel. In the proposed method, four secret data bits are mapped with the four most significant bits of a cover pixel. Furthermore, the only two LSBs of a pixel are modified to indicate the mapping strategy. Experimental results show that the proposed method is able to achieve 3.48% larger embedding capacity while enhancing the visual quality (i.e., peak signal to noise ratio (PSNR) 3.73 dB) and reducing the modification of 0.76 bits per pixel. Moreover, the proposed method provides security against basic Regular and Singular groups (RS) steganalysis and histogram steganalysis detection attacks.

Image Steganography Using DWT and Semi Hexadecimal Code Based on PSNR

2018 ◽  
Vol 6 (8) ◽  
pp. 230
Author(s):  
Balkar Singh
Keyword(s):  
Visual Quality ◽  
Threshold Value ◽  
Image Steganography ◽  
Cover Image ◽  
Discrete Wavelet ◽  
Secret Data ◽  
Stego Image ◽  
Pixel Value ◽  
Better Than

In this paper, a novel image steganography approach is proposed to enhance the visual quality of stego image. The cover image is decomposed using Discrete Wavelet Transform (DWT) to produce wavelet subbands and threshold value is calculated for each higher frequency wavelet subbands. Wavelet coefficients having magnitude larger than the threshold of its subband are selected to embed the secret data. Semi Hexadecimal Code (SHC) is proposed to convert pixel value of secret image into smaller equivalent value so that it distorts stego image as less as possible. Experimental results shows that maximum PSNR between cover image and stego image is more than 75 dB .Proposed approach is also compared with the existing approaches and this comparison shows that the proposed approach is better than the existing approaches. 

scholarly journals A New Reversible Data Hiding Technique Combined with Interpolation and Pixel Value Differencing Method

2020 ◽  
pp. 53-58
Author(s):  
Jayeeta Majumder ◽  
Chittaranjan Pradhan
Keyword(s):  
High Capacity ◽  
Main Idea ◽  
Image Steganography ◽  
Second Phase ◽  
Secret Data ◽  
Stego Image ◽  
Hiding Capacity ◽  
Small Distortion ◽  
Pixel Value ◽  
Pixel Value Differencing

Steganography is the popular security method that provides complete security for communicating secret details. Image steganography is a very interesting field because of the imperceptible way of hiding data in images, since small distortion in the images cannot be identified by a human eye. This is the main idea to develop image steganography algorithms to improve visual quality. Pixel Value Differencing is able to provide a high quality stego image in spite of the high capacity of the concealed information. This paper proposes the first the interpolation techniques with the pixel block then applying then the Pixel Value Differencing method. Here in the first phase the original image is portioned into 2X2 block then applying the nearest neighbour interpolation technique after that in the second phase PVD is used to embed the secret data. Then the new pixel value of the neighbouring pixel also calculated. In this paper one variant are proposed by using single range table. We observed that for both the variant PSNR value and the hiding capacity are increased.

scholarly journals Taylor expansion based stereo image reversible data hiding

2020 ◽  
Author(s):  
Xinyang Ying ◽  
Guobing Zhou
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Taylor Expansion ◽  
Stereo Image ◽  
Embedding Capacity ◽  
Stereo Images ◽  
Secret Data ◽  
Stego Image ◽  
Multi Level

Abstract The reversible data hiding allows original image to be completely recovered from the stego image when the secret data has been extracted, it is has drawn a lot of attentions from researchers. In this paper, a novel Taylor Expansion (TE) based stereo image reversible data hiding method is presented. Since the prediction accuracy is essential to the data hiding performance, a novel TE based predictor using correlations of two views of the stereo image is proposed. TE can fully exploit strong relationships between matched pixels in the stereo image so that the accuracy of the prediction can be improved. Then, histogram shifting is utilized to embed data to decrease distortion of stereo images, and multi-level hiding can increase embedding capacity. Experimental results show that the proposed method is superior to some existing data hiding methods considering embedding capacity and the quality of the stego stereo images.

scholarly journals Data-Hiding Scheme Using Multidirectional Pixel-Value Differencing on Colour Images

2019 ◽  
Vol 2019 ◽  
pp. 1-11
Author(s):  
Pyung-Han Kim ◽  
Eun-Jun Yoon ◽  
Kwan-Woo Ryu ◽  
Ki-Hyun Jung
Keyword(s):  
Data Hiding ◽  
Vision System ◽  
Experimental Results ◽  
Human Vision ◽  
Embedding Capacity ◽  
Secret Data ◽  
Colour Image ◽  
Pixel Value ◽  
The Difference ◽  
Pixel Value Differencing

Data hiding is a technique that hides the existence of secret data from malicious attackers. In this paper, we propose a new data-hiding scheme using multidirectional pixel-value differencing, which can embed secret data in two directions or three directions on colour images. The cover colour image is divided into nonoverlapping blocks, and the pixels of each block are decomposed into R, G, and B channels. The pixels of each block perform regrouping, and then the minimum pixel value within each block is selected. The secret data can be embedded into two directions or three directions based on the minimum pixel value by using the difference value for the block. The pixel pairs with the embedded secret data are put separately into two stego images for secret data extraction on receiver sides. In the extraction process, the secret data can be extracted using the difference value of the two stego images. Experimental results show that the proposed scheme has the highest embedding capacity when the secret data are embedded into three directions. Experimental results also show that the proposed scheme has a high embedding capacity while maintaining the degree of distortion that cannot be perceived by human vision system for two directions.

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 High Capacity Multilevel Image Steganography

2016 ◽  
Vol 25 (08) ◽  
pp. 1650091 ◽  
Author(s):  
Geeta Kasana ◽  
Kulbir Singh ◽  
Satvinder Singh Bhatia
Keyword(s):  
Digital Images ◽  
High Capacity ◽  
Block Size ◽  
Visual Quality ◽  
Cover Image ◽  
Embedding Capacity ◽  
Secret Data ◽  
Block Based ◽  
High Embedding Capacity

This paper proposes a block-based high capacity steganography technique for digital images. The cover image is decomposed into blocks of equal size and the largest pixel of each block is found to embed the secret data bits and also the smallest pixel of each block is used for embedding to enhance the capacity. Embedding of secret data is performed using the concept that the pixel of a cover image has only two states — even and odd. Multilevel approach is also combined in the proposed technique to achieve high embedding capacity. In order to make the proposed technique more secure, a key is generated using embedding levels, block size, pixel embedding way, encryption parameters, and starting blocks of each embedding levels. Embedding capacity and visual quality of stego images generated by the proposed steganography technique are higher than the existing techniques. Steganalysis tests have been performed to show the un-detectability and imperceptibility of the proposed technique.

scholarly journals Information Trouncing Via Slightest Momentous Spot System Procedure

2018 ◽  
Vol 7 (3.27) ◽  
pp. 488
Author(s):  
D Saravanan ◽  
N Sivaprasad ◽  
Dennis Joseph
Keyword(s):  
Visual Quality ◽  
Secret Message ◽  
Pseudorandom Number Generator ◽  
Least Significant Bit ◽  
Pixel Value ◽  
The Difference ◽  
Pixel Value Differencing ◽  
The Relationship ◽  
Embedding Rate

The least-significant-bit based approach is a popular type of stenographic algorithms in the spatial domain. However, we find that in most existing approaches, the choice of embedding positions within a cover audio mainly depends on a pseudorandom number generator without considering the relationship between the audio content itself and the size of the secret message. In this paper, we expand the least significant bit matching revisited audio stegnography and propose an edge adaptive scheme which can select the embedding regions according to the size of secret message and the difference between two consecutive pixels in the cover audio. For lower embedding rates, only sharper edge regions are used while keeping the other smoother regions as they are. When the embedding rate increases, more edge regions can be released adaptively for data hiding by adjusting just a few parameters. New scheme can enhance the security significantly compared with typical least significant bit-based approaches as well as their edge adaptive ones, such as pixel-value-differencing-based approaches, while preserving higher visual quality of stegno audios at the same time.  

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