A steganography embedding method based on edge identification and XOR coding

• Published in: Expert systems with applications 2016-03, Vol.46, p.293-306
• Main Authors: Al-Dmour, Hayat, Al-Ani, Ahmed
• Format: Article
• Language: English
• Subjects: Algorithms; Coding; Edge detection; Human Visual System (HVS); Image detection; Image quality; IWT; Messages; Steganography; XOR coding
• ISSN: 0957-4174; 1873-6793
• DOI: 10.1016/j.eswa.2015.10.024

•A method for hiding data in the spatial or IWT domains of images is proposed.•Design new edge detection method to estimate same edge intensities for both images.•XOR operation is used to embed the message and to improve imperceptibility.•Proposed method is robust against textural feature steganalysis. In this paper, we present a novel image steganography algorithm that combines the strengths of edge detection and XOR coding, to conceal a secret message either in the spatial domain or an Integer Wavelet Transform (IWT) based transform domain of the cover image. Edge detection enables the identification of sharp edges in the cover image that when embedding in would cause less degradation to the image quality compared to embedding in a pre-specified set of pixels that do not differentiate between sharp and smooth areas. This is motivated by the fact that the human visual system (HVS) is less sensitive to changes in sharp contrast areas compared to uniform areas of the image. The edge detection method presented here is capable of estimating the exact edge intensities for both the cover and stego images (before and after embedding the message), which is essential when extracting the message. The XOR coding, on the other hand, is a simple, yet effective, process that helps in reducing differences between the cover and stego images. In order to embed three secret message bits, the algorithm requires four bits of the cover image, but due to the coding mechanism, no more than two of the four bits will be changed when producing the stego image. The proposed method utilizes the sharpest regions of the image first and then gradually moves to the less sharp regions. Experimental results demonstrate that the proposed method has achieved better imperceptibility results than other popular steganography methods. Furthermore, when applying a textural feature steganalytic algorithm to differentiate between cover and stego images produced using various embedding rates, the proposed method maintained a good level of security compared to other steganography methods.