Significant Bits Of Cover Image Research Articles

Hiding data in images using steganography techniques with compression algorithms

Steganography is the science and art of secret communication between two sides that attempt to hide the content of the message. It is the science of embedding information into the cover image without causing a loss in the cover image after embedding.Steganography is the art and technology of writing hidden messages in such a manner that no person, apart from the sender and supposed recipient, suspects the lifestyles of the message. It is gaining huge attention these days as it does now not attract attention to its information's existence. In this paper, a comparison of two different techniques is given. The first technique used Least Significant Bit (LSB) with no encryption and no compression. In the second technique, the secret message is encrypted first then LSB technique is applied. Moreover, Discrete Cosine Transform (DCT) is used to transform the image into the frequency domain. The LSB algorithm is implemented in spatial domain in which the payload bits are inserted into the least significant bits of cover image to develop the stego-image while DCT algorithm is implemented in frequency domain in which the stego-image is transformed from spatial domain to the frequency domain and the payload bits are inserted into the frequency components of the cover image.The performance of these two techniques is evaluated on the basis of the parameters MSE and PSNR.

Transmission of Hidden Cipher Text over a Binary Symmetric Channel

A new high capacity and robust image steganography method based on human vision sensitivity is introduced. Kohonen Neural network is trained according to the contrast sensitivity of pixels present in cover image. Trained network classify the pixels of cover image in different levels of sensitivity. Data embedding is performed by LSB substitution method, which replaces the least significant bits of cover image with secret information that would be embedded. But prior to embedding, cryptography is applied on text. We used Optimal Pixel Adjustment Process (OPAP) to obtain an optimal mapping function to reduce the difference error between the original image and the stego-image, therefore improving the hiding capacity with low distortions. On the destination side, the original image is not needed for extracting the embedded data. Convolution Code are also used to improve performance of existing algorithm over binary symmetric channel (BSC). It is observed that the capacity and security is increased with acceptable PSNR in the proposed algorithm compared to the existing algorithm.