Adaptive speech compression based on AMBTC

Most of the AMBTC-based RDH (absolute instantaneous block truncation) schemes Cannot be decrypted because AMBTC, which is unknown to most device. Also, some of the RDH methods based on AMBTC. But the load capacity obtained is low. For this purpose, in this work, a scalable RDH scheme based on AMBTC was introduced from the AMBTC zip code. In contrast to the decoder-based AMBTC-based RDH methods that are only able to achieve a constant payload for adjust the audio. Due to its advantages, sound pressure has attracted a great deal of attention in the last 20 years. The main developments concern transmission requirements and storage capacity. The need for high-quality audio data has been increased due to sudden improvements in computer manufacturers and technologies. Therefore, the developments include speech compression technologies, in which the two compression classes are lossless. This paper aims to review techniques for specification compression methods using AMBTC (a momentary absolute block truncation notation based ) method, and to summarize their importance and uses

Robo-line storage: Low latency, high capacity storage systems over geographically distributed networks

Rapid advances in high performance computing are making possible more complete and accurate computer-based modeling of complex physical phenomena, such as weather front interactions, dynamics of chemical reactions, numerical aerodynamic analysis of airframes, and ocean-land-atmosphere interactions. Many of these 'grand challenge' applications are as demanding of the underlying storage system, in terms of their capacity and bandwidth requirements, as they are on the computational power of the processor. A global view of the Earth's ocean chlorophyll and land vegetation requires over 2 terabytes of raw satellite image data. In this paper, we describe our planned research program in high capacity, high bandwidth storage systems. The project has four overall goals. First, we will examine new methods for high capacity storage systems, made possible by low cost, small form factor magnetic and optical tape systems. Second, access to the storage system will be low latency and high bandwidth. To achieve this, we must interleave data transfer at all levels of the storage system, including devices, controllers, servers, and communications links. Latency will be reduced by extensive caching throughout the storage hierarchy. Third, we will provide effective management of a storage hierarchy, extending the techniques already developed for the Log Structured File System. Finally, we will construct a protototype high capacity file server, suitable for use on the National Research and Education Network (NREN). Such research must be a Cornerstone of any coherent program in high performance computing and communications

Data hiding techniques in steganography using fibonacci sequence and knight tour algorithm

The foremost priority in the information and communication technology era, is achieving an efficient and accurate steganography system for hiding information. The developed system of hiding the secret message must capable of not giving any clue to the adversaries about the hidden data. In this regard, enhancing the security and capacity by maintaining the Peak Signal-to-Noise Ratio (PSNR) of the steganography system is the main issue to be addressed. This study proposed an improved for embedding secret message into an image. This newly developed method is demonstrated to increase the security and capacity to resolve the existing problems. A binary text image is used to represent the secret message instead of normal text. Three stages implementations are used to select the pixel before random embedding to select block of (64 × 64) pixels, follows by the Knight Tour algorithm to select sub-block of (8 × 8) pixels, and finally by the random pixels selection. For secret embedding, Fibonacci sequence is implemented to decomposition pixel from 8 bitplane to 12 bitplane. The proposed method is distributed over the entire image to maintain high level of security against any kind of attack. Gray images from the standard dataset (USC-SIPI) including Lena, Peppers, Baboon, and Cameraman are implemented for benchmarking. The results show good PSNR value with high capacity and these findings verified the worthiness of the proposed method. High complexities of pixels distribution and replacement of bits will ensure better security and robust imperceptibility compared to the existing systems in the literature

Improved Watermarking Algorithm Based on Discrete Wavelet Transform and Fibonacci Permutation

Digital image watermark is an imperceptible, robust, secure message embedded into the image, which identify one or more owner, distributor, or recipient of the image, origin or status of the data or transaction dates. Watermarking is also used for data hiding, content labeling, broadcast monitoring, and integrity control applications. Digital watermarking resembles communication systems. Watermark is the sent message. Image is the watermark channel or carrier. Image pixels and possible attacks on marked image constitute the noise. Only the authorized parties' extracts the watermark message from the marked image by using detector. Digital watermarking has three major requirements. Watermark should be robust against noise and attacks, imperceptible and has the required capacity. These three requirements conflict with each other. To illustrate, increasing the watermark strength makes the system more robust but unfortunately decreases the perceptual quality. As a second example, increasing the capacity of the watermark decreases the robustness. In this thesis, the goal was to study digital image watermarking and develop watermarking algorithm that can achieve high imperceptibility, maximum capacity, and high robustness against image manipulation at the same time. This algorithm is based on the combination of Fibonacci permutation and discrete wavelet transforms (DWT). A binary image is used as the watermark and inserted into a mid-frequency wavelet subband of the permuted image. The watermarked image is reproduced by taking the inverse DWT and the inverse permutation. In extraction process the watermark is extracted from the watermarked image directly without using the original image. The experimental results have shown that the proposed watermark is invisible to human eyes and very robust against image manipulation, such as JPEG compression, median filtering, wiener filtering, and noises

Optical image compression and encryption methods

International audienceOver the years extensive studies have been carried out to apply coherent optics methods in real-time communications and image transmission. This is especially true when a large amount of information needs to be processed, e.g., in high-resolution imaging. The recent progress in data-processing networks and communication systems has considerably increased the capacity of information exchange. However, the transmitted data can be intercepted by nonauthorized people. This explains why considerable effort is being devoted at the current time to data encryption and secure transmission. In addition, only a small part of the overall information is really useful for many applications. Consequently, applications can tolerate information compression that requires important processing when the transmission bit rate is taken into account. To enable efficient and secure information exchange, it is often necessary to reduce the amount of transmitted information. In this context, much work has been undertaken using the principle of coherent optics filtering for selecting relevant information and encrypting it. Compression and encryption operations are often carried out separately, although they are strongly related and can influence each other. Optical processing methodologies, based on filtering, are described that are applicable to transmission and/or data storage. Finally, the advantages and limitations of a set of optical compression and encryption methods are discussed

Algorithm engineering : string processing

The string matching problem has attracted a lot of interest throughout the history of computer science, and is crucial to the computing industry. The theoretical community in Computer Science has a developed a rich literature in the design and analysis of string matching algorithms. To date, most of this work has been based on the asymptotic analysis of the algorithms. This analysis rarely tell us how the algorithm will perform in practice and considerable experimentation and fine-tuning is typically required to get the most out of a theoretical idea. In this thesis, promising string matching algorithms discovered by the theoretical community are implemented, tested and refined to the point where they can be usefully applied in practice. In the course of this work we have presented the following new algorithms. We prove that the time complexity of the new algorithms, for the average case is linear. We also compared the new algorithms with the existing algorithms by experimentation. " We implemented the existing one dimensional string matching algorithms for English texts. From the findings of the experimental results we identified the best two algorithms. We combined these two algorithms and introduce a new algorithm. " We developed a new two dimensional string matching algorithm. This algorithm uses the structure of the pattern to reduce the number of comparisons required to search for the pattern. " We described a method for efficiently storing text. Although this reduces the size of the storage space, it is not a compression method as in the literature. Our aim is to improve both space and time taken by a string matching algorithm. Our new algorithm searches for patterns in the efficiently stored text without decompressing the text. " We illustrated that by pre-processing the text we can improve the speed of the string matching algorithm when we search for a large number of patterns in a given text. " We proposed a hardware solution for searching in an efficiently stored DNA text

WAVELET BASED DATA HIDING OF DEM IN THE CONTEXT OF REALTIME 3D VISUALIZATION (Visualisation 3D Temps-Réel à Distance de MNT par Insertion de Données Cachées Basée Ondelettes)

The use of aerial photographs, satellite images, scanned maps and digital elevation models necessitates the setting up of strategies for the storage and visualization of these data. In order to obtain a three dimensional visualization it is necessary to drape the images, called textures, onto the terrain geometry, called Digital Elevation Model (DEM). Practically, all these information are stored in three different files: DEM, texture and position/projection of the data in a geo-referential system. In this paper we propose to stock all these information in a single file for the purpose of synchronization. For this we have developed a wavelet-based embedding method for hiding the data in a colored image. The texture images containing hidden DEM data can then be sent from the server to a client in order to effect 3D visualization of terrains. The embedding method is integrable with the JPEG2000 coder to accommodate compression and multi-resolution visualization. Résumé L'utilisation de photographies aériennes, d'images satellites, de cartes scannées et de modèles numériques de terrains amène à mettre en place des stratégies de stockage et de visualisation de ces données. Afin d'obtenir une visualisation en trois dimensions, il est nécessaire de lier ces images appelées textures avec la géométrie du terrain nommée Modèle Numérique de Terrain (MNT). Ces informations sont en pratiques stockées dans trois fichiers différents : MNT, texture, position et projection des données dans un système géo-référencé. Dans cet article, nous proposons de stocker toutes ces informations dans un seul fichier afin de les synchroniser. Nous avons développé pour cela une méthode d'insertion de données cachées basée ondelettes dans une image couleur. Les images de texture contenant les données MNT cachées peuvent ensuite être envoyées du serveur au client afin d'effectuer une visualisation 3D de terrains. Afin de combiner une visualisation en multirésolution et une compression, l'insertion des données cachées est intégrable dans le codeur JPEG 2000

Using RGB colour combination in coloured quick response (QR) code algorithm to enhance QR code capacity

A Quick Response (QR) Code is a two-dimensional barcode that stores characters and can be read by any smartphone camera. The QR code has the capability to encode various data formats and languages; nevertheless, existing black and white QR code offers limited data storage. Even though there exist research on coloured QR Code to increase the storage capacity, requirement for larger data capacity by end user keep increasing. Hence, this thesis proposes a coloured QR Code algorithm which utilizes RGB colour combination to allow a larger data storage. The proposed algorithm integrates the use of compression, multiplexing, and multilayer techniques in encoding and decoding the QR code. Furthermore, it also introduces a partial encoding/decoding algorithm that allows the stored data to be manipulated. The algorithm that includes encoding and decoding processes is based on the red, green, and blue (RGB) colour techniques, which are used to create high capacity coloured QR code. This is realised in the experiments that store American Standard Code for Information Interchange (ASCII) characters. The ASCII text characters are used as an input and performance is measured by the number of characters that can be stored in a single black and white QR code version 40 (i.e. the benchmark) and also the coloured QR code. Other experiment metrics include percentage of missing characters, number of produced QR code, and elapsed time to create the QR code. Simulation results indicate that the proposed algorithm stores 29 times more characters than the black and white QR code and 9 times more than other coloured QR code. Hence, this shows that the coloured QR Code has the potential of becoming a useful mini-data storage as it does not rely on internet connection