In this paper, method of steganography in Audio is introduced for hiding secret data in audio media file (WAV). Hiding in audio becomes a challenging discipline, since the Human Auditory System is extremely sensitive. The proposed method is to embed the secret text message in frequency domain of audio file. The proposed method contained two stages: the first embedding phase and the second extraction phase. In embedding phase the audio file transformed from time domain to frequency domain using 1-level linear wavelet decomposition technique and only high frequency is used for hiding secreted message. The text message encrypted using Data Encryption Standard (DES) algorithm. Finally; the Least Significant bit (LSB) algorithm used to hide secret message in high frequency. The proposed approach tested in different sizes of audio file and showed the success of hiding according to (PSNR) equation.
Mit dem Fall der Berliner Mauer am 9. November 1989 und dem damit
einhergehenden Verschwinden der DDR aus der politischen Bühne im Jahre 1990
„haben sich nicht nur politische Systeme umgewälzt, sondern auch die Menschen
in ihnen haben ihre Maßstäbe und Perspektiven geändert, unter ihnen Kunstrichter
und Leser.“1 Alles, was bis zum Tag der Wiedervereinigung im Bereich der Kultur
galt, fiel über den Haufen.2 Christa Wolf, die in der DDR eine Leitfigur des
öffentlichen und kulturellen Lebens war und an der Spitze der einflussreichen
Schriftsteller stand, landete im vereinigten Deutschland „immerhin noch auf Platz
25, ein erstaunliches Resultat nach all den Vorwürfen“3, die gegen ihr Werk und
ihre m
Image compression is one of the data compression types applied to digital images in order to reduce their high cost for storage and/or transmission. Image compression algorithms may take the benefit of visual sensitivity and statistical properties of image data to deliver superior results in comparison with generic data compression schemes, which are used for other digital data. In the first approach, the input image is divided into blocks, each of which is 16 x 16, 32 x 32, or 64 x 64 pixels. The blocks are converted first into a string; then, encoded by using a lossless and dictionary-based algorithm known as arithmetic coding. The more occurrence of the pixels values is codded in few bits compare with pixel values of less occurre
... Show MoreIn this paper, a compression system with high synthetic architect is introduced, it is based on wavelet transform, polynomial representation and quadtree coding. The bio-orthogonal (tap 9/7) wavelet transform is used to decompose the image signal, and 2D polynomial representation is utilized to prune the existing high scale variation of image signal. Quantization with quadtree coding are followed by shift coding are applied to compress the detail band and the residue part of approximation subband. The test results indicate that the introduced system is simple and fast and it leads to better compression gain in comparison with the case of using first order polynomial approximation.
With wireless sensor network (WSN) wide applications in popularity, securing its data becomes a requirement. This can be accomplished by encrypting sensor node data. In this paper a new an efficient symmetric cryptographic algorithm is presented. This algorithm is called wireless sensor network wavelet curve ciphering system (WSN-WCCS). The algorithm idea based on discrete wavelet transformation to generate keys for each node in WSN. It implements on hierarchical clustering WSN using LEACH protocol. Python programming language version 2.7 was used to create the simulator of WSN framework and implement a WSN-WCCS algorithm. The simulation result of the proposed WSN-WCCS with other symmetric algorithms has show
... Show MoreIn this paper, a method is proposed to increase the compression ratio for the color images by
dividing the image into non-overlapping blocks and applying different compression ratio for these
blocks depending on the importance information of the block. In the region that contain important
information the compression ratio is reduced to prevent loss of the information, while in the
smoothness region which has not important information, high compression ratio is used .The
proposed method shows better results when compared with classical methods(wavelet and DCT).
Dans le romantisme et ses textes, il est important de mentionner qu'il n'existe qu'un seul thème romantique qui est l'amour, mais assez pour avoir fait du XIXème siècle, une révolution du texte romantique. L'amour consiste à la réduction de l'univers, à un seul être, puis la dilatation de ce seul être, voilà l'amour. cet amour passionnel n'est qu'un arrangement froid et réfléchi excluant d'emblée l'exaltation des sentiments. Néanmoins, cet amour passionnel peut être brutal. quant à la mort, dans le drame romantique, l'amour et la mort sont liés. Beaucoup d'histoires d'amour finissent le plus souvent par un suicide passionnel : le romantique cherche à l'atteindre par l'amour un sentiment sanctifié, et divinisé ; mais c
... Show MoreDans le romantisme et ses textes, il est important de mentionner qu'il n'existe qu'un seul thème romantique qui est l'amour, mais assez pour avoir fait du XIXème siècle, une révolution du texte romantique. L'amour consiste à la réduction de l'univers, à un seul être, puis la dilatation de ce seul être, voilà l'amour. cet amour passionnel n'est qu'un arrangement froid et réfléchi excluant d'emblée l'exaltation des sentiments. Néanmoins, cet amour passionnel peut être brutal. quant à la mort, dans le drame romantique, l'amour et la mort sont liés. Beaucoup d'histoires d'amour finissent le plus souvent par un suicide passionnel : le romantique cherche à l'atteindre par l'amour un sentiment sanctifié, et divinisé ; mais c
... Show MoreAbstract
In this research we study the wavelet characteristics for the important time series known as Sunspot, on the aim of verifying the periodogram that other researchers had reached by the spectral transform, and noticing the variation in the period length on one side and the shifting on another.
A continuous wavelet analysis is done for this series and the periodogram in it is marked primarily. for more accuracy, the series is partitioned to its the approximate and the details components to five levels, filtering these components by using fixed threshold on one time and independent threshold on another, finding the noise series which represents the difference between
... Show More