Information security in data storage and transmission is increasingly important. On the other hand, images are used in many procedures. Therefore, preventing unauthorized access to image data is crucial by encrypting images to protect sensitive data or privacy. The methods and algorithms for masking or encoding images vary from simple spatial-domain methods to frequency-domain methods, which are the most complex and reliable. In this paper, a new cryptographic system based on the random key generator hybridization methodology by taking advantage of the properties of Discrete Cosine Transform (DCT) to generate an indefinite set of random keys and taking advantage of the low-frequency region coefficients after the DCT stage to pass them to a subsystem consisting of an Reversible Logic Gate (RLG) group to obtain the secret keys that are passed to Rivest Shamir Adleman (RSA) to finish encrypting the image. The results indicate that the proposed method has the ability to generate a very large set of highly complex and secure secret keys that can be used later in the encryption stage. Moreover, the number and complexity of those keys will change each time the image is changed, and this represents the contribution of the proposed method. They experienced no time loss throughout the encryption and decryption processes when using RLG, which indicates that the proposed system did a good job in making different keys from the same image. And it differs in the strength of the key from one image to another, depending on the nature of the color imge.
Static Synchronous Series Compensator (SSSC) is a well known device for effectively regulating the active power flow in a power system. In this paper, the SSSC linearized power flow equations are incorporated into Newton-Raphson algorithm in a MATLAB written program to investigate the control of active poweer flow and the transient stability of a five bus and a thirty bus IEEE test systems, during abnormal conduction (three phase fault near buses). A comparison of the results obtained for the base case without SSSC and with it to investigate the effectiveness of the device on both of the active power flow and the transient stability.
In this paper, we will present proposed enhance process of image compression by using RLE algorithm. This proposed yield to decrease the size of compressing image, but the original method used primarily for compressing a binary images [1].Which will yield increasing the size of an original image mostly when used for color images. The test of an enhanced algorithm is performed on sample consists of ten BMP 24-bit true color images, building an application by using visual basic 6.0 to show the size after and before compression process and computing the compression ratio for RLE and for the enhanced RLE algorithm.
In this research, an analysis for the standard Hueckel edge detection algorithm behaviour by using three dimensional representations for the edge goodness criterion is presents after applying it on a real high texture satellite image, where the edge goodness criterion is analysis statistically. The Hueckel edge detection algorithm showed a forward exponential relationship between the execution time with the used disk radius. Hueckel restrictions that mentioned in his papers are adopted in this research. A discussion for the resultant edge shape and malformation is presented, since this is the first practical study of applying Hueckel edge detection algorithm on a real high texture image containing ramp edges (satellite image).
In recent years, with the rapid development of the current classification system in digital content identification, automatic classification of images has become the most challenging task in the field of computer vision. As can be seen, vision is quite challenging for a system to automatically understand and analyze images, as compared to the vision of humans. Some research papers have been done to address the issue in the low-level current classification system, but the output was restricted only to basic image features. However, similarly, the approaches fail to accurately classify images. For the results expected in this field, such as computer vision, this study proposes a deep learning approach that utilizes a deep learning algorithm.
... Show MoreFractal image compression depends on representing an image using affine transformations. The main concern for researches in the discipline of fractal image compression (FIC) algorithm is to decrease encoding time needed to compress image data. The basic technique is that each portion of the image is similar to other portions of the same image. In this process, there are many models that were developed. The presence of fractals was initially noticed and handled using Iterated Function System (IFS); that is used for encoding images. In this paper, a review of fractal image compression is discussed with its variants along with other techniques. A summarized review of contributions is achieved to determine the fulfillment of fractal ima
... Show MoreGypseous soil is prevalent in arid and semi-arid areas, is from collapsible soil, which contains the mineral gypsum, and has variable properties, including moisture-induced volume changes and solubility. Construction on these soils necessitates meticulous assessment and unique designs due to the possibility of foundation damage from soil collapse. The stability and durability of structures situated on gypseous soils necessitate close collaboration with specialists and careful, methodical preparation. It had not been done to find the pattern of failure in the micromechanical behavior of gypseous sandy soil through particle image velocity (PIV) analysis. This adopted recently in geotech
In this work, satellite images for Razaza Lake and the surrounding area
district in Karbala province are classified for years 1990,1999 and
2014 using two software programming (MATLAB 7.12 and ERDAS
imagine 2014). Proposed unsupervised and supervised method of
classification using MATLAB software have been used; these are
mean value and Singular Value Decomposition respectively. While
unsupervised (K-Means) and supervised (Maximum likelihood
Classifier) method are utilized using ERDAS imagine, in order to get
most accurate results and then compare these results of each method
and calculate the changes that taken place in years 1999 and 2014;
comparing with 1990. The results from classification indicated that
The study aims to introduce the Islamic sites available on the Internet and determine the criteria that contribute to evaluating these sites to indicate their value, topics, and services, while evaluating a simple random sample of the general Islamic sites, which number (35) sites. The results were presented in (8) tables. The study concluded To a set of conclusions, including: (465) “Islamic” websites were seized during the research period, and they are constantly increasing. They were classified according to the name of the website (domain name) com, org, net, edu, and also according to topics such as general Islamic websites and websites of holy places. Mosques, sites of sheikhs, etc. Among the best general Islamic websites are: Isla
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