Two-in-One Image Steganography Using Error Diffusion

Ruixi Dong,Kiichi Urahama,Kenji Hara,Kohei Inoue

doi:10.12792/jiiae.7.42

Abstract

Image steganography is a technique for concealing a secret message in a cover image unobtrusively. The resultant images are called the stego images. In this paper, we propose a method for concealing a secret image into a cover image of the same size, where the most significant bits (MSBs) of the secret image are embedded in the least significant bits (LSBs) of the cover image after the reversal of the order of the bit sequences. Such a symmetric relationship between MSBs and LSBs derives a complementary between the stego and extracted secret images. We also propose a method for improving the image quality of both stego and extracted secret images by using an error diffusion technique. Experimental results show that the proposed method works well for both grayscale and color images, and the proposed error diffusion method can suppress the noises like false contours caused in the embedding process visually and quantitatively.

Highlights

The developments of information technology in recent years have demanded secure communication among the information technology equipments and the users
We propose a two-in-one image steganography method which conceals a secret image into a cover image of the same size in an least significant bits (LSBs) steganography approach, where 4 most significant bits (MSBs) of the secret image are embedded in the corresponding 4 LSBs of the cover image after the reversal of the order of the bit sequence of the 4 MSBs
The proposed method is based on a least significant bit (LSB) approach, where the most significant bits (MSBs) of the secret image are embedded in the LSBs of the cover image after the reversal of the order of the bit sequences

Summary

Introduction

The developments of information technology in recent years have demanded secure communication among the information technology equipments and the users. Hiding information, such as copyright messages and serial numbers, is a promising technique for information security, and has recently become important in a number of application areas [1]. Information hiding techniques include two subdisciplines: watermarking and steganography [2]. Steganalysis is a counterpart of steganography, and has been extensively studied in the last decade [5]. Xia et al proposed an improved version of Gabor filter residual (GFR) steganalysis [6]. Qian et al proposed a paradigm for steganalysis to learn features automatically via deep learning models [5]. Agarwal and Farid detected manipulations such as insertion, removal, rotation and airbrushing from JPEG dimples [7]

Results

Discussion

Conclusion