Improving Quality of Stego Images through Dithering Techniques for Pixel Pair Matching Steganographic Schemes
S. Arivazhagan1, W. Sylvia Lilly Jebarani2, S. Ananthi Roy3, E. Amrutha4
1S. Arivazhagan*, Department of Electronics and Communication Engineering, MEPCO Schlenk Engineering College, Sivakasi, (Tamil Nadu), India.
2W.Sylvia Lilly Jebarani, Department of Electronics and Communication Engineering, MEPCO Schlenk Engineering College, Sivakasi, (Tamil Nadu), India.
3S. Ananthi Roy, Department of Electronics and Communication Engineering, MEPCO Schlenk Engineering College, Sivakasi, (Tamil Nadu), India.
4E. Amrutha, Department of Electronics and Communication Engineering, MEPCO Schlenk Engineering College, Sivakasi, (Tamil Nadu), India.
Manuscript received on July 20, 2019. | Revised Manuscript received on August 10, 2019. | Manuscript published on August 30, 2019. | PP: 4923-4931 | Volume-8 Issue-6, August 2019. | Retrieval Number: F9239088619/2019©BEIESP | DOI: 10.35940/ijeat.F9239.088619
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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: Steganography plays a vital role in sending any covert data via public media without hiding the covert channel. Due to visually imperceptible embedding process of secret, it is able to escape visual attacks. But when it is suspected, steganography can be detected by any efficient steganalysis techniques. It is an important aspect to improve the security of stego image if the information hidden is highly confidential, by improving the stego image quality. This paper presents a comprehensive analysis of deploying dithering (diffusion) techniques for enhancing the quality of stego images created by various Pixel Pair matching (PPM) steganographic algorithms. The dithering process attempts to keep the difference between original cover image and secret embedded stego image to a very minimum value. The quality of stego images is evaluated on parameters such as Peak Signal to Noise Ratio (PSNR), Structural SIMilarity index (SSIM), Net Pixel Change Rate (NPCR) and Unified Averaged Changed Intensity (UACI). Experimental results show that, depending on the type of steganographic algorithm used, the behaviour of dithering techniques differ and the choice of dithering must be made considering computational complexity of dithering process also.
Keywords: Steganography, Pixel Pair Matching, Stego image, Dithering, Error diffusion.