A novel steganography approach for audio files

We present a novel robust and secure steganography technique to hide images into audio files aiming at increasing the carrier medium capacity. The audio files are in the standard WAV format, which is based on the LSB algorithm while images are compressed by the GMPR technique which is based on the Discrete Cosine Transform (DCT) and high frequency minimization encoding algorithm. The method involves compression-encryption of an image file by the GMPR technique followed by hiding it into audio data by appropriate bit substitution. The maximum number of bits without significant effect on audio signal for LSB audio steganography is 6 LSBs. The encrypted image bits are hidden into variable and multiple LSB layers in the proposed method. Experimental results from observed listening tests show that there is no significant difference between the stego audio reconstructed from the novel technique and the original signal. A performance evaluation has been carried out according to quality measurement criteria of Signal-to-Noise Ratio (SNR) and Peak Signal-to-Noise Ratio (PSNR)

Data compression for the microgravity experiments

Researchers present the environment and conditions under which data compression is to be performed for the microgravity experiment. Also presented are some coding techniques that would be useful for coding in this environment. It should be emphasized that researchers are currently at the beginning of this program and the toolkit mentioned is far from complete

Importance of Dimensionality Reduction in Image Processing

This paper presents a survey on various techniques of compression methods. Linear Discriminant analysis (LDA) is a method used in statistics, pattern recognition and machine learning to find a linear combination of features that classifies an object into two or more classes. This results in a dimensionality reduction before later classification.Principal component analysis (PCA) uses an orthogonal transformation to convert a set of correlated variables into a set of values of linearly uncorrelated variables called principal components. The purpose of the review is to explore the possibility of image compression for multiple images

An Image Steganography Algorithm for Hiding Data Based on HDWT, LZW and OPAP

Image steganography is the art of information hiding, which embeds a secret data into a cover image. However, high capacity of secret data and high quality of stego image are key issues in image steganography. In this paper, an image steganography technique based on Haar Discrete Wavelet Transform (HDWT), Lempel Ziv Welch (LZW) algorithm and Optimal Pixel Adjustment Process (OPAP) is proposed. The HDWT is used to increase the robustness of stego image against attacks. To increase the hidden capacity, LZW algorithm is performed on the secret message. The OPAP is then applied to reduce the embedding error between the cover image and stego image. The experimental results are evaluated by four standard images as covers, and with two types of secret messages. The results demonstrate high visual quality of stego image with large Hidden Capacity (HC) of secret data compared with recent technique

Detection of Motion Vector-Based Video Steganography by Adding or Subtracting One Motion Vector Value

In last decades the Steganography is an tremendous progress, at the same time there exist issues to detect the steganalysis in motion based video where the substance is reliably in motion conduct that makes that to detect it. Analyzing the difference between the rated motion value plays a crucial role that enables us to focus on difference between the locally optimal SAD and actual SAD after adding-or-subtracting-one operation on the motion value. Based on the motion vectors to play out the classification and extraction process at last, two features sets are been used based on the fact that most motion vectors are locally optimal for most video codec’s to complete this process. The conventional approaches announced the technique for proposed prevails to meet the requirement applications and detecting the steganalysis in videos compare in the literature

From Theory to Practice: Plug and Play with Succinct Data Structures

Engineering efficient implementations of compact and succinct structures is a time-consuming and challenging task, since there is no standard library of easy-to- use, highly optimized, and composable components. One consequence is that measuring the practical impact of new theoretical proposals is a difficult task, since older base- line implementations may not rely on the same basic components, and reimplementing from scratch can be very time-consuming. In this paper we present a framework for experimentation with succinct data structures, providing a large set of configurable components, together with tests, benchmarks, and tools to analyze resource requirements. We demonstrate the functionality of the framework by recomposing succinct solutions for document retrieval.Comment: 10 pages, 4 figures, 3 table