Edge Adaptive Steganography Using DWT
Ajinkya S. Jamdar1, Atul V. Shah2, D. D. Gavali3, S. L. Kurkute4
1Mr. Ajinkya S. Jamdar, faculty at Navsahyadri Group of Institution’s Faculty of Engineering, Naigaon, Pune, India.
2Prof. Atul V. Shah, Assistant Professor at the Department of Electronics & Telecommunication Engineering, Maharashtra, India.
3Prof. Dhananjay D. Gavali, Assistant Professor & Head of the Department of Electrical Engineering, Naigaon, Pune, India.
4Prof. Sanjay L. Kurkute, Associate Professor in the Department of Electronics & Telecommunication Engineering, Pune, India.
Manuscript received on March 02, 2013. | Revised Manuscript received on April 13, 2013. | Manuscript published on April 30, 2013. | PP:648-652 | Volume-2, Issue-4, April 2013. | Retrieval Number: D1559042413/2013©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The least-significant-bit (LSB)-based approach is a popular type of Steganography algorithms in the spatial domain. The least-significant-bit (LSB)-based approach is a popular type of steganographic algorithms in the spatial domain. However, we find that in most existing approaches, the choice of embedding positions within a cover image mainly depends on a pseudorandom number generator without considering the relationship between the image content itself and the size of the secret message. Thus the smooth/flat regions in the cover images will inevitably be contaminated after data hiding even at a low embedding rate, and this will lead to poor visual quality and low security based on our analysis and extensive experiments, especially for those images with many smooth regions. In this paper, we expand the LSB matching revisited image steganography 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 image. 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. The experimental results evaluated on 6000 natural images with three specific and four universal steganalysis algorithms show that the new scheme can enhance the security significantly compared with typical LSB-based approaches as well as their edge adaptive ones, such as pixel-value-differencing-based approaches, while preserving higher visual quality of stego images at the same time.
Keywords: LSB, DWT, Secret Message, Pixel.