A secure high capacity full-gray-scale-level multi-image information hiding and secret image authentication scheme via Tchebichef moments

2013 ◽  
Vol 28 (5) ◽  
pp. 531-552 ◽  
Author(s):  
S.M. Elshoura ◽  
D.B. Megherbi
Keyword(s):  
Information Hiding ◽  
High Capacity ◽  
Image Authentication ◽  
Authentication Scheme ◽  
Gray Scale ◽  
Scale Level ◽  
Image Information ◽  
Secret Image ◽  
Tchebichef Moments

scholarly journals A Novel High-Capacity Information Hiding Scheme Based on Improved U-Net

2022 ◽  
Vol 2022 ◽  
pp. 1-12
Author(s):  
Lianshan Liu ◽  
Lingzhuang Meng ◽  
Weimin Zheng ◽  
Yanjun Peng ◽  
Xiaoli Wang
Keyword(s):  
Processing Speed ◽  
Information Hiding ◽  
High Capacity ◽  
Network Size ◽  
Visual Effect ◽  
Secret Image ◽  
Gradual Introduction ◽  
Research Goal ◽  
Carrier Image ◽  
Multiscale Image Analysis

With the gradual introduction of deep learning into the field of information hiding, the capacity of information hiding has been greatly improved. Therefore, a solution with a higher capacity and a good visual effect had become the current research goal. A novel high-capacity information hiding scheme based on improved U-Net was proposed in this paper, which combined improved U-Net network and multiscale image analysis to carry out high-capacity information hiding. The proposed improved U-Net structure had a smaller network scale and could be used in both information hiding and information extraction. In the information hiding network, the secret image was decomposed into wavelet components through wavelet transform, and the wavelet components were hidden into image. In the extraction network, the features of the hidden image were extracted into four components, and the extracted secret image was obtained. Both the hiding network and the extraction network of this scheme used the improved U-Net structure, which preserved the details of the carrier image and the secret image to the greatest extent. The simulation experiment had shown that the capacity of this scheme was greatly improved than that of the traditional scheme, and the visual effect was good. And compared with the existing similar solution, the network size has been reduced by nearly 60%, and the processing speed has been increased by 20%. The image effect after hiding the information was improved, and the PSNR between the secret image and the extracted image was improved by 6.3 dB.

scholarly journals Review of Steganography Algorithms

2020 ◽  
pp. 01-09
Author(s):  
Ali Mohammed Ahmed ◽  
Ibrahim Mahmood Rashid
Keyword(s):  
Information Hiding ◽  
High Capacity ◽  
Vital Role ◽  
Hidden Information ◽  
Image Information ◽  
Secret Communication ◽  
File Formats ◽  
Hide Information ◽  
Other Information ◽  
Audio Video

The ability to hide plays a vital role in effective secret communication. This is achieved by hiding information (Steganography). The science of concealing information is the science of concealing information in other information so that it appears that hidden information is not something to the human eye. There are many ways to hide information within an image, audio / video, document, etc. But hiding information in pictures has its own characteristics and is the most popular among others. This paper provides a review of several methods, such as image field and conversion field algorithms available to implement image information hiding (Steganography). In this paper, high-capacity information hidings schemes are analyzed for different file formats. Secret communication is done before Password encryption to protect information. The intended recipient will decrypt the information using this password.

scholarly journals A New Method of Image Steganography Using 7th Bit of a Pixel as Indicator by Introducing the Successive Temporary Pixel in the Gray Scale Image

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Kamaldeep Joshi ◽  
Swati Gill ◽  
Rajkumar Yadav
Keyword(s):  
Image Coding ◽  
Information Hiding ◽  
High Capacity ◽  
Image Steganography ◽  
New Method ◽  
The Internet ◽  
Mathematical Function ◽  
Sensitive Information ◽  
Gray Scale ◽  
Gray Scale Image

As the internet has become the medium for transferring the sensitive information, the security of the transferred message has become the utmost priority. Image steganography has emerged out as the eminent tool of information hiding that ensures the security of the transmitted data. Image files provide high capacity, and their frequency of availability over the internet is also high. In this paper, a method of image coding is proposed that hides the information along a selected pixel and on the next value of the selected pixel, that is, pixel + 1. One bit is hidden at the selected pixel, and the second bit is hidden on the pixel +1 value. On the basis of the 7th bit of the pixels of an image, a mathematical function is applied at the 7th bit of the pixels, which generates a temporary variable (pixel + 1). The 7th bit of the selected pixel and 7th bit of pixel + 1 are used for information hiding and extraction. On the basis of a combination of these two values, two bits of the message can be hidden on each pixel. After implementation, the efficiency of the method is checked on the basis of parameters like PSNR and MSE, and then comparison with some already proposed techniques was done. This proposed image steganography showed interesting, promising results when compared with other existing techniques.

A Visual Hiding Algorithm Based on Human Visual System

2014 ◽  
Vol 989-994 ◽  
pp. 2393-2397
Author(s):  
Rui Dong ◽  
Dao Shun Wang
Keyword(s):  
Visual System ◽  
Human Visual System ◽  
Information Hiding ◽  
Image Information ◽  
Secret Image ◽  
Secret Information ◽  
Texture Information

Image information hiding is a way of concealing secret information within another image or file. The previous researches of image information hiding extract secret by calculating. An algorithm based on HVS (Human Visual System) is proposed in this paper. We first decide the embedding region and embedding strength of secret image based on edge and texture information. Then, a pair of invert images is chosen as the cover images, and the stego images are constructed by modifying the pixels of the cover images through the proposed criterion. Correspondingly, the secret image can be recovered through overlaying the two stego images.

scholarly journals High Capacity Blind Information Hiding Based on Autoencoder

2021 ◽  
Vol 1802 (3) ◽  
pp. 032027
Author(s):  
Zhenjie Bao ◽  
Yadong Jin ◽  
Yue Liu ◽  
Jingyun Hu
Keyword(s):  
Information Hiding ◽  
High Capacity

scholarly journals Flip Extended Visual Cryptography for Gray-Scale and Color Cover Images

Symmetry ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 65
Author(s):  
Lu Wang ◽  
Bin Yan ◽  
Hong-Mei Yang ◽  
Jeng-Shyang Pan
Keyword(s):  
Privacy Protection ◽  
Visual Cryptography ◽  
Color Images ◽  
Cover Image ◽  
Error Diffusion ◽  
Gray Scale ◽  
Secret Image ◽  
Transaction Security

Visual cryptography (VC) has found numerous applications in privacy protection, online transaction security, and voting security, etc. To counteract potential cheating attacks, Lin et al. proposed flip visual cryptography in 2010, where a second secret image can be revealed by stacking one share with a flipped version of another share. The second secret image can be designed as an additional verification mechanism. However, Lin’s scheme produces meaningless shares and is only applicable to binary secret images. It is interesting to explore whether it is possible to extend the flip VC to having cover images (i.e., extended VC) and these cover images are color images. This problem is challenging since too many restricting conditions need to be met. In this paper, we designed a flip VC for gray-scale and color cover images based on constraint error diffusion. We show that it is possible to meet all the constraints simultaneously. Compared with existing schemes, our scheme enjoys the following features: Color cover images, no computation needed for decoding, and no interference from cover image on the recovered secret image.

Sign in / Sign up

Export Citation Format

Share Document