3 research outputs found
Reversible Data Hiding Scheme with High Embedding Capacity Using Semi-Indicator-Free Strategy
A novel reversible data-hiding scheme is proposed to embed secret data into a side-matched-vector-quantization- (SMVQ-) compressed image and achieve lossless reconstruction of a vector-quantization- (VQ-) compressed image. The rather random distributed histogram of a VQ-compressed image can be relocated to locations close to zero by SMVQ prediction. With this strategy, fewer bits can be utilized to encode SMVQ indices with very small values. Moreover, no indicator is required to encode these indices, which yields extrahiding space to hide secret data. Hence, high embedding capacity and low bit rate scenarios are deposited. More specifically, in terms of the embedding rate, the bit rate, and the embedding capacity, experimental results show that the performance of the proposed scheme is superior to those of the former data hiding schemes for VQ-based, VQ/SMVQ-based, and search-order-coding- (SOC-) based compressed images
Secure Image Steganography using Cryptography and Image Transposition
Information security is one of the most challenging problems in today's
technological world. In order to secure the transmission of secret data over
the public network (Internet), various schemes have been presented over the
last decade. Steganography combined with cryptography, can be one of the best
choices for solving this problem. This paper proposes a new steganographic
method based on gray-level modification for true colour images using image
transposition, secret key and cryptography. Both the secret key and secret
information are initially encrypted using multiple encryption algorithms
(bitxor operation, bits shuffling, and stego key-based encryption); these are,
subsequently, hidden in the host image pixels. In addition, the input image is
transposed before data hiding. Image transposition, bits shuffling, bitxoring,
stego key-based encryption, and gray-level modification introduce five
different security levels to the proposed scheme, making the data recovery
extremely difficult for attackers. The proposed technique is evaluated by
objective analysis using various image quality assessment metrics, producing
promising results in terms of imperceptibility and security. Moreover, the high
quality stego images and its minimal histogram changeability, also validate the
effectiveness of the proposed approach.Comment: A simple but effective image steganographic method, providing secure
transmission of secret data over Internet. The final published version of the
paper can be downloaded from the link:
(http://www.neduet.edu.pk/NED-Journal/2015/15vol4paper3.html). Please contact
me at [email protected] if you need the final formatted published
version of the pape
Investigating the Effect of Block Length on the Performance of Fractal Coding Using Audio Files
The goal of compression techniques is to reducing the size of data and decreasing the communication cost while transferring data. Fractal based coding technique is widely used to compress images files which provides high compression ratio and good image quality. However, like a compression technique, it is still limited because of the difference of the human perceptions between audio and image files, the long time for searching the best possible domain blocks and many comparisons in the encoding process. For those reasons, Fractal Coding had not broadly studied on audio data. Few years ago, Fractal Coding has been extended to apply on the audio data. In this paper, the application of the Fractal Coding on different types of audio files is investigated. Moreover, the effect of block length on the audio quality and compression performance are highlighted since block length is considered the main factor in the Fractal Coding algorithm. A GTZAN dataset is adopted in the evaluation and the experimental results show that there is an inverse relationship between block length and audio quality and proportional relationship between block length and compression ratio and factor. Furthermore, it can be noticed that the Fractal Coding can be compressed any speech and music audio signal directly with acceptable quality, PSNR 39 dB on average with a high compression ratio around 90 % with compression factor around 10 when the block length is 20 samples