scholarly journals Pixel-Value-Ordering based Reversible Information Hiding Scheme with Self-Adaptive Threshold Strategy

Symmetry ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 764 ◽  
Author(s):  
Tzu-Chuen Lu ◽  
Chun-Ya Tseng ◽  
Shu-Wen Huang ◽  
Thanh Nhan
Keyword(s):  
Image Quality ◽  
Block Size ◽  
Adaptive Threshold ◽  
Secret Message ◽  
Threshold Strategy ◽  
Hiding Capacity ◽  
Hide Information ◽  
Reversible Information Hiding ◽  
Pixel Value ◽  
The Difference

Pixel value ordering (PVO) hiding scheme is a kind of data embedding technique that hides a secret message in the difference of the largest and second largest pixels of a block. After that, the scholars improved PVO scheme by using a threshold to determine whether the block is smooth or complex. Only a smooth block can be used to hide information. The researchers analyzed all the possible thresholds to find the proper one for hiding secret message. However, it is time consuming. Some researchers decomposing the smooth block into four smaller blocks for hiding more messages to increase image quality. However, the complexity of the block is more important than block size. Hence, this study proposes an ameliorated method. The proposed scheme analyzes the variation of the region so as to judge the complexity of the block and applies quantification strategy to quantified the pixel for making sure the pixel is reversible. It adopts an adaptive threshold generation mechanism to find the proper threshold for different images. The results show that the image quality of the proposed scheme is higher than that of the other methods. The proposed scheme can also let the user adjust the hiding rate to achieve higher image quality or hiding capacity.

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.  

A Secure Data-Hiding Approach Using Particle Swarm Optimization and Pixel Value Difference

2016 ◽  
pp. 363-381
Author(s):  
Tanmoy Halder ◽  
Sunil Karforma ◽  
Rupali Halder
Keyword(s):  
Particle Swarm Optimization ◽  
Data Hiding ◽  
Particle Swarm ◽  
Secret Message ◽  
Secret Data ◽  
Swarm Optimization ◽  
Pixel Value ◽  
The Difference ◽  
Block Based ◽  
Pixel Value Difference

In this chapter a novel data hiding approach by combining Particle Swarm Optimization (PSO) and Pixel Value Difference (PVD) has been proposed. Pixel-Value-Difference (PVD) method of Steganography uses the difference between pixels within an image to hide secret data. The proposed method is a block-based adaptive steganographic approach, which selects M×N block of pixels from cover image and embed secret message within pixels using Pixel-value-difference and LSB substitution method. PSO is used to select most appropriate areas within the image for hiding secret information. Results obtained using the approach show that distortion due to data embedding is negligible. The proposed approach is compared with existing methods in terms of bits per pixel. This method could be applied to hide any digital secret data for secure transfer over internet.

scholarly journals High-Capacity and High-Quality Reversible Data Hiding Method Using Recurrent Round-Trip Embedding Strategy in the Quotient Image

2021 ◽  
Vol 11 (21) ◽  
pp. 10157
Author(s):  
Chin-Feng Lee ◽  
Hua-Zhe Wu
Keyword(s):  
Image Quality ◽  
Data Hiding ◽  
Information Hiding ◽  
Reversible Data Hiding ◽  
High Capacity ◽  
Secret Message ◽  
Embedding Capacity ◽  
Round Trip ◽  
Pixel Value ◽  
Embedding Strategy

In previous research, scholars always think about how to improve the information hiding algorithm and strive to have the largest embedding capacity and better image quality, restoring the original image. This research mainly proposes a new robust and reversible information hiding method, recurrent robust reversible data hiding (triple-RDH), with a recurrent round-trip embedding strategy. We embed the secret message in a quotient image to increase the image robustness. The pixel value is split into two parts, HiSB and LoSB. A recurrent round-trip embedding strategy (referred to as double R-TES) is designed to adjust the predictor and the recursive parameter values, so the pixel value carrying the secret data bits can be first shifted to the right and then shifted to the left, resulting in pixel invariance, so the embedding capacity can be effectively increased repeatedly. Experimental results show that the proposed triple-RDH method can effectively increase the embedding capacity up to 310,732 bits and maintain a certain level of image quality. Compared with the existing pixel error expansion (PEE) methods, the triple-RDH method not only has a high capacity but also has robustness for image processing against unintentional attacks. It can also be used for capacity and image quality according to the needs of the application, performing adjustable embedding.

scholarly journals A Stochastic Model for Block Segmentation of Images Based on the Quadtree and the Bayes Code for It

Entropy ◽  
2021 ◽  
Vol 23 (8) ◽  
pp. 991
Author(s):  
Yuta Nakahara ◽  
Toshiyasu Matsushima
Keyword(s):  
Computational Cost ◽  
Block Size ◽  
Input Image ◽  
Generative Model ◽  
Image Size ◽  
Variable Block ◽  
General Data ◽  
The Difference ◽  
Segmentation Of Images ◽  
Target Data

In information theory, lossless compression of general data is based on an explicit assumption of a stochastic generative model on target data. However, in lossless image compression, researchers have mainly focused on the coding procedure that outputs the coded sequence from the input image, and the assumption of the stochastic generative model is implicit. In these studies, there is a difficulty in discussing the difference between the expected code length and the entropy of the stochastic generative model. We solve this difficulty for a class of images, in which they have non-stationarity among segments. In this paper, we propose a novel stochastic generative model of images by redefining the implicit stochastic generative model in a previous coding procedure. Our model is based on the quadtree so that it effectively represents the variable block size segmentation of images. Then, we construct the Bayes code optimal for the proposed stochastic generative model. It requires the summation of all possible quadtrees weighted by their posterior. In general, its computational cost increases exponentially for the image size. However, we introduce an efficient algorithm to calculate it in the polynomial order of the image size without loss of optimality. As a result, the derived algorithm has a better average coding rate than that of JBIG.

scholarly journals Efficient Image Watermarking Using Filtered DWT-Blocks for Quantization of Significant Differences

2014 ◽  
Vol 4 (1-2) ◽  
Author(s):  
Thien Huynh-The ◽  
Thuong Le-Tien ◽  
Tuan Nguyen-Thanh
Keyword(s):  
Image Watermarking ◽  
Histogram Equalization ◽  
Adaptive Threshold ◽  
Parent Child Relationship ◽  
Child Relationship ◽  
Low Pass ◽  
The Difference ◽  
Block Based ◽  
Robust Blind Watermarking ◽  
Relationship Of

In the paper, a robust blind watermarking method is introduced for gray-scale images based on wavelet tree quantization with an adaptive threshold in the extraction. Every block of 2×2 coefficients of High-Low subbands of the Wavelet tranform are grouped in a block through the parent-child relationship of the wavelet tree. Every scrambled binary watermark bit is embedded into each block based on the difference value of two largest coefficients. The watermark is recovered by comparing the difference values in each block to an adaptive threshold. The accuracy of an extracted watermark depends on the threshold which is determined by minimizing the sum of weighted within-class variance. The performance of the proposed watermarking method is represented through experimental results under various types of attack such as, Histogram Equalization, Cropping, Low-pass Filtering, Gaussian noise, Salt & Pepper noise and JPEG compression. In additions, the proposed method is also compared to recent methods in the extraction performance.

scholarly journals Secure Data Transfer over Internet Using Image Steganography: Review

2021 ◽  
pp. 33-52
Author(s):  
Dakhaz Mustafa Abdullah ◽  
Siddeeq Y. Ameen ◽  
Naaman Omar ◽  
Azar Abid Salih ◽  
Dindar Mikaeel Ahmed ◽  
...  
Keyword(s):  
Digital Media ◽  
Private Information ◽  
Data Transfer ◽  
Well Being ◽  
Discrete Wavelet ◽  
Transform Domain ◽  
Least Significant Bit ◽  
Discrete Cosine Transformation ◽  
Hide Information ◽  
Pixel Value

Whether it's for work or personal well-being, keeping secrets or private information has become part of our everyday existence. Therefore, several researchers acquire an entire focus on secure transmitting secret information. Confidential information is collectively referred to as Steganography for inconspicuous digital media such as video, audio, and images. In disguising information, Steganography plays a significant role. Traditional Steganography faces a further concern of discovery as steganalysis develops. The safety of present steganographic technologies thus has to be improved. In this research, some of the techniques that have been used to hide information inside images have been reviewed. According to the hiding domain, these techniques can be divided into two main parts: The spatial Domain and Transform Domain. In this paper, three methods for each Domain have been chosen to be studied and evaluated. These are; Least Significant Bit (LSB), Pixel Value Difference (PVD), Exploiting Modification Direction (EMD), contourlet transform, Discrete Wavelet Transformation (DWT), and, Discrete Cosine Transformation (DCT). Finally, the best results that have been obtained in terms of higher PSNR, Capacity, and more robustness and security are discussed.

scholarly journals Video steganography based on DCT psychovisual and object motion

2020 ◽  
Vol 9 (3) ◽  
pp. 1015-1023 ◽  
Author(s):  
Muhammad Fuad ◽  
Ferda Ernawan
Keyword(s):  
Video Quality ◽  
Object Motion ◽  
Multimedia Data ◽  
Secret Message ◽  
Hiding Capacity ◽  
Video Steganography ◽  
Limited Bandwidth ◽  
Video Frames ◽  
Dct Coefficients ◽  
Video Reconstruction

Steganography is a technique of concealing the message in multimedia data. Multimedia data, such as videos are often compressed to reduce the storage for limited bandwidth. The video provides additional hidden-space in the object motion of image sequences. This research proposes a video steganography scheme based on object motion and DCT-psychovisual for concealing the message. The proposed hiding technique embeds a secret message along the object motion of the video frames. Motion analysis is used to determine the embedding regions. The proposed scheme selects six DCT coefficients in the middle frequency using DCT-psychovisual effects of hiding messages. A message is embedded by modifying middle DCT coefficients using the proposed algorithm. The middle frequencies have a large hiding capacity and it relatively does not give significant effect to the video reconstruction. The performance of the proposed video steganography is evaluated in terms of video quality and robustness against MPEG compression. The experimental results produce minimum distortion of the video quality. Our scheme produces a robust of hiding messages against MPEG-4 compression with average NC value of 0.94. The proposed video steganography achieves less perceptual distortion to human eyes and it's resistant against reducing video storage.

Reversible Information Hiding and Its Application to Image Authentication

2013 ◽  
pp. 238-257 ◽  
Author(s):  
Masaaki Fujiyoshi ◽  
Hitoshi Kiya
Keyword(s):  
Information Hiding ◽  
Prediction Error ◽  
Image Authentication ◽  
Original Image ◽  
Distorted Image ◽  
New Class ◽  
Hide Information ◽  
Reversible Information Hiding ◽  
Location Map

This chapter addresses a new class of Reversible Information Hiding (RIH) and its application to verifying the integrity of images. The method of RIH distorts an image once to hide information in the image itself, and it not only extracts embedded information but also recovers the original image from the distorted image. The well-known class of RIH is based on the expansion of prediction error in which a location map, which indicates the pixel block positions of a certain block category, is required to recover the original image. In contrast, the method described in this chapter is free from having to memorize any parameters including location maps. This feature suits the applications of image authentication in which the integrity of extracted information guarantees that of a suspected image. If image-dependent parameters such as location maps are required, the suspected image should first be identified from all possible images. The method described in this chapter reduces such costly processes.

Improved Capacity Image Steganography Algorithm using 16-Pixel Differencing with n-bit LSB Substitution for RGB Images

2016 ◽  
Vol 6 (6) ◽  
pp. 2735 ◽  
Author(s):  
Meenakshi S Arya ◽  
Meenu Rani ◽  
Charndeep Singh Bedi
Keyword(s):  
Digital Media ◽  
Daily Basis ◽  
Image Steganography ◽  
The Internet ◽  
Least Significant Bit ◽  
Content Protection ◽  
Hiding Capacity ◽  
Pixel Value ◽  
Four Levels ◽  
Lsb Substitution

<p>With the intrusion of internet into the lives of every household and terabytes of data being transmitted over the internet on daily basis, the protection of content being transmitted over the internet has become an extremely serious concern. Various measures and methods are being researched and devised everyday to ensure content protection of digital media. To address this issue of content protection, this paper proposes an RGB image steganography based on sixteen-pixel differencing with n-bit Least Significant Bit (LSB) substitution. The proposed technique provides higher embedding capacity without sacrificing the imperceptibility of the host data. The image is divided into 4×4 non overlapping blocks and in each block the average difference value is calculated. Based on this value the block is classified to fall into one of four levels such as, lower, lower-middle, higher-middle and higher. If block belongs to lower level then 2-bit LSB substitution is used in it. Similarly, for lower-middle, higher-middle and higher level blocks 3, 4, and 5 bit LSB substitution is used. In our proposed method there is no need of pixel value readjustment for minimizing distortion. The experimental results show that stego-images are imperceptible and have huge hiding capacity.</p>

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