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.

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 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.

scholarly journals Image Steganography Using Pixel Value Differencing (PVD) Technique Based on Firefly Algorithm

2021 ◽  
pp. 80-86
Author(s):  
Oluwaseun M. Alade ◽  
Elizabeth A. Amusan ◽  
Oluyinka T. Adedeji ◽  
Oluwaseun O. Alo
Keyword(s):  
Firefly Algorithm ◽  
Promising Result ◽  
Signal To Noise Ratio ◽  
Text Message ◽  
Image Steganography ◽  
Cover Image ◽  
Experimental Result ◽  
Stego Image ◽  
Pixel Value ◽  
Pixel Value Differencing

Steganography deals with the ways of hiding communicated data in such a way that it remains confidential. Finding best position inside cover image to embed text message, maintaining a reasonable trade-off between security, robustness, higher bit embedding rate and imperceptibility are some of the challenges of steganography system. Hence, this paper presents firefly algorithm for finding best positions inside cover image in order to embed text message into cover image using Pixel Value Differencing (PVD) technique. Four different cover image was used. Experimental result showed the cover image with selected location using firefly algorithm as well as the stego image using PVD technique. The stego image was evaluated using Peak Signal to Noise Ratio (PSNR) and Mean square Error (MSE).  Firefly Algorithm with PVD technique produced a promising result for image steganography.

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 High Security and Capacity of Image Steganography for Hiding Human Speech Based on Spatial and Cepstral Domains

2020 ◽  
Vol 8 (1) ◽  
pp. 95
Author(s):  
Yazen A. Khaleel
Keyword(s):  
Speech Signal ◽  
Vocal Tract ◽  
Color Image ◽  
Signal To Noise Ratio ◽  
Image Steganography ◽  
Mel Frequency Cepstral Coefficients ◽  
Secret Data ◽  
Stego Image ◽  
Hiding Capacity ◽  
Original Speech

A new technique of hiding a speech signal clip inside a digital color image is proposed in this paper to improve steganography security and loading capacity. The suggested technique of image steganography is achieved using both spatial and cepstral domains, where the Mel-frequency cepstral coefficients (MFCCs) are adopted, as very efficient features of the speech signal. The presented technique in this paper contributes to improving the image steganography features through two approaches. First is to support the hiding capacity by the usage of the extracted MFCCs features and pitches extracted from the speech signal and embed them inside the cover color image rather than directly hiding the whole samples of the digitized speech signal. Second is to improve the data security by hiding the secret data (MFCCs features) anywhere in the host image rather than directly using the least significant bits substitution of the cover image. At the recovering side, the proposed approach recovers these hidden features and using them to reconstruct the speech waveform again by inverting the steps of MFCCs extraction to recover an approximated vocal tract response and combine it with recovered pitch based excitation signal. The results show a peak signal to noise ratio of 52.4 dB of the stego-image, which reflect a very good quality and a reduction ratio of embedded data to about (6%–25%). In addition, the results show a speech reconstruction degree of about 94.24% correlation with the original speech signal.

scholarly journals High Capacity Image Steganography using Pixel Value Differencing Method with Data Compression using Neural Network

2019 ◽  
Vol 8 (12) ◽  
pp. 1800-1804
Keyword(s):  
Neural Network ◽  
Data Compression ◽  
Data Hiding ◽  
Image Steganography ◽  
Data Embedding ◽  
Least Significant Bit ◽  
Secret Data ◽  
Stego Image ◽  
Compression Technique ◽  
Hiding Capacity

The Digital Market Is Rapidly Growing Day By Day. So, Data Hiding Is Going To Increase Its Importance. Information Can Be Hidden In Different Embedding Mediums, Known As Carriers By Using Steganography Techniques. The Carriers Are Different Multimedia Medium Such As Images, Audio Files, Video Files, And Text Files .There Are Several Techniques Present To Achieve Data Hiding Like Least Significant Bit Insertion Method And Transform Domain Technique. The Data Hidden Capacity Inside The Cover Image Totally Depends On The Properties Of The Image Like Number Of Noisy Pixels. Data Compression Provides To Hide Large Amount Of Secret Data To Increase The Capacity And The Image Steganography Based On Any Neural Network Provides That The Size And Quality Of The Stego-Image Remains Unaltered After Data Embedding. In This Paper We Propose A New Method Combined With Data Compression Along With Data Embedding Technique And After Embedding To Maintain The Quality The Communication Channel Use The Neural Network. The Compression Technique Increase The Data Hiding Capacity And The Use Of Neural Network Maintain The Flow Of Data Processing Signal

scholarly journals A High-Capacity Image Steganography Method Using Chaotic Particle Swarm Optimization

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Aya Jaradat ◽  
Eyad Taqieddin ◽  
Moad Mowafi
Keyword(s):  
Particle Swarm Optimization ◽  
Image Quality ◽  
High Capacity ◽  
Particle Swarm ◽  
Image Steganography ◽  
Embedding Capacity ◽  
Secret Data ◽  
Stego Image ◽  
Swarm Optimization ◽  
Chaotic Particle Swarm Optimization

Image steganography has been widely adopted to protect confidential data. Researchers have been seeking to improve the steganographic techniques in order to increase the embedding capacity while preserving the stego-image quality. In this paper, we propose a steganography method using particle swarm optimization and chaos theory aiming at finding the best pixel locations in the cover image to hide the secret data while maintaining the quality of the resultant stego-image. To enhance the embedding capacity, the host and secret images are divided into blocks and each block stores an appropriate amount of secret bits. Experimental results show that the proposed scheme outperforms existing methods in terms of the PSNR and SSIM image quality metrics.

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 An Improved Image Steganography Algorithm Based on PVD

2018 ◽  
Vol 10 (2) ◽  
pp. 569 ◽  
Author(s):  
Sharif Shah Newaj Bhuiyan ◽  
Norun Abdul Malek ◽  
Othman Omran Khalifa ◽  
Farah Diyana Abdul Rahman
Keyword(s):  
Image Steganography ◽  
Secret Data ◽  
Data Value ◽  
Maximum Payload ◽  
Pixel Value ◽  
Simulation Results ◽  
Encoding Method ◽  
Pixel Value Differencing ◽  
Bit Plane Slicing ◽  
Better Than

In this paper, a modification of PVD (Pixel value differencing) algorithm is used for Image Steganography in spatial domain. It is normalizing secret data value by encoding method to make the new pixel edge difference less among three neighbors (horizontal, vertical and diagonal) and embedding data only to less intensity pixel difference areas or regions. The proposed algorithm shows a good improvemernt for both color and gray-scale images compared to other algorithms. Color images performance are better than gray images. However, in this work the focus is mainly on gray images. The strenght of this scheme is that any random hidden/secret data do not make any shuttle differences to Steg-image compared to original image. The bit plane slicing is used to analyze the maximum payload that has been embeded into the cover image securely. The simulation results show that the proposed algorithm is performing better and showing great consistent results for PSNR, MSE values of any images, also against Steganalysis attack.

Sign in / Sign up

Export Citation Format

Share Document