Binary Text-Image Steganography

TLDR: This dissertation has tried to obtain the secret image from stego image without having cover image, considering secret image as noise, and compared with the existing method using PSNR, MSE, NCC, MAD, SC as comparison parameters.

Abstract: Unlike encryption, steganography hides the very existence of secret information rather than hiding its meaning only. Image based steganography is the most common system used since digital images are widely used over the Internet and Web. The main aim of steganography is to increase the steganographic capacity and enhance the imperceptibility or undetectability. However, steganographic capacity and imperceptibility are at odds with each other. In addition, there is a tradeoff between both steganographic capacity and stego image quality. Hiding more data in cover images (higher capacity) introduces more artefacts into cover images and then increases the perceptibility of hidden data . Furthermore, it is not possible to simultaneously maximize the security and capacity of a steganographic system. Therefore, increasing steganographic capacity and enhancing stego image quality are still challenges. Secret image extraction is done by the proposed technique in which first the cover image is recovered by noise removal methods and then applying alpha blending. Since peak signal-to- noise ratio (PSNR) is extensively used as a quality measure of stego images, the reliability of PSNR for stego images is also evaluated in the work described in this dissertation. The proposed work is compared with the existing method using PSNR, MSE, NCC, MAD, SC as comparison parameters. Proposed technique reduces the requirement to keep record of cover images for secret information extraction. Otherwise for each information received, the receiver should also have the cover image saved with him. In the proposed technique I have tried to obtain the secret image from stego image without having cover image, considering secret image as noise. The technique deals with steganography in wavelet domain. Complete work can be seen as adding noise to cover image, and then using noise removal technique to obtain secret image. Soft thresholding and bilateral filtering used for removing noise are efficient. Experimental results shows that there's a trade - off between stego image and secret image extracted. It is seen that as we increase the value of alpha, stego image degrades, but secret image improves. The secret image obtained is in visually acceptable form. Results shown are objective and subjective in nature.