The Moving Object Detection and Research Effects of Noise on Images Based on Cellular Automata With a Hexagonal Coating Form and Radon Transform

Methods for image identification based on the Radon transform using hexagonal-coated cellular automata in the chapter are considered. A method and a mathematical model for the detection of moving objects based on hexagonal-coated cellular automata are described. The advantages of using hexagonal coverage for detecting moving objects in the image are shown. The technique of forming Radon projections for moving regions in the image, which is designed for a hexagonal-coated cellular automata, is described. The software and hardware implementation of the developed methods are presented. Based on the obtained results, a hexagonal-coated cellular automata was developed to identify images of objects based on the Radon transform. The Radon transform allowed to effectively extract the characteristic features of images with a large percentage of noise. Experimental analysis showed the advantages of the proposed methods of image processing and identification of moving objects.

Protection of Information From the Influence of Noise on the Transmission of Video Data in a Geoinformation System

The chapter describes parallel-hierarchical technologies that are characterized by a high degree of parallelism, high performance, noise immunity, parallel-hierarchical mode of transmission and processing of information. The peculiarities of the design of automated geoinformation and energy systems on the basis of parallel-hierarchical technologies and modified confidential method of Q-transformation of information are presented. Experimental analysis showed the advantages of the proposed methods of image processing and extraction of characteristic features.

Association Rule-Mining-Based Intrusion Detection System With Entropy-Based Feature Selection

Intrusion detection system (IDSs) are important to industries and organizations to solve the problems of networks, and various classifiers are used to classify the activity as malicious or normal. Today, the security has become a decisive part of any industrial and organizational information system. This chapter demonstrates an association rule-mining algorithm for detecting various network intrusions. The KDD dataset is used for experimentation. There are three input features classified as basic features, content features, and traffic features. There are several attacks are present in the dataset which are classified into Denial of Service (DoS), Probe, Remote to Local (R2L), and User to Root (U2R). The proposed method gives significant improvement in the detection rates compared with other methods. Association rule mining algorithm is proposed to evaluate the KDD dataset and dynamic data to improve the efficiency, reduce the false positive rate (FPR) and provides less time for processing.

Identification System for Moving Objects Based on Parallel Shift Technology

There are tasks of automatic identification of the moving stock of the railway, one of which is the automatic identification of rail cars cars by their number plates. Different organizational, legal, moral and ethical, technical, and programmatic methods of automated identification are used to solve this problem. At present little attention is paid to the development of means of automatic identification of moving objects, which would be possible regardless of the orientation and shape of the figure, especially if it concerns the recognition of freely oriented images of number plates. Therefore, many new methods for recognizing of number plates are developing. In the chapter, the system of identification of objects by their number plates in real time is considered. On moving objects (moving stock of a railway), an identifier image is drawn, which is an ordered set of characters. As a rule, these are numbers. But there may be other characters. The work also discusses the method of identification images of number plates with a high percentage of noise.

Methods for Extracting the Skeleton of an Image Based on Cellular Automata With a Hexagonal Coating Form and Radon Transform

The chapter describes a brief history of the emergence of the theory of cellular automata, their main properties, and methods for constructing. The image skeletonization methods based on the Euler zero differential are described. The advantages of using hexagonal coverage for detecting moving objects in the image are shown. The software and hardware implementation of the developed methods are presented. Based on the obtained results, a hexagonal-coated cellular automata was developed to identify images of objects based on the Radon transform. The method and mathematical model of the selection of characteristic features for the selection of the skeleton and implementation on cellular automata with a hexagonal coating are described. The Radon transform allowed to effectively extract the characteristic features of images with a large percentage of noise. An experiment for different images with different noises was conducted. Experimental analysis showed the advantages of the proposed methods of image processing and extraction of characteristic features.

Towards Intelligent Data Processing for Automated Determination of Information System Assets

The chapter discusses how the intelligent data processing techniques, namely, the event correlation, can be used for automated discovery of information system assets. The authors believe that solving of this task will allow more accurate and detailed construction of the risk model for cyber security assessment. This task is complicated by the features of configuration and operation of modern information systems. The chapter describes different types of event analysis, including statistical, structural, dynamic, applied to this task. The authors propose a technique that incorporates determining the types of object characteristics, the types of objects (system assets), and their hierarchy based on the statistical analysis of system events. Significant attention is given to the stage of source data pre-processing. In addition, the developed technique has the broad application prospects to discover the inappropriate, dubious, and harmful information. The case studies and experiments that demonstrate an application of the developed technique are provided and analyzed.

Research of Methods of Steganographic Protection of Audio Information Based on Video Containers

The chapter describes investigations of steganographic methods of information protection, which use containers represented by files in AVI format. MP3 audio files are selected as data that is embedded in the used container. For the introduction of audio data, the video container was divided into control and information parts. Secret data were embedded in the information part of the video file, which did not lead to distortions when the container file is played. Studies have been conducted to find repetitive blocks in the structure of a video container. The chapter analyzed the determination of the amount of embedded data for containers with different parameters: color saturation, video file resolution, video file length, compression quality, and frames per second. An algorithm has been developed for the introduction and extraction of information represented by sound formats.

SOFM for Image Compression Based on Spatial Frequency Band-Pass Filter and Vector Quantization

This chapter presents image compression based on SOFM and vector quantization (VQ). The purpose of this chapter is to show the significance of SOFM with bandpass filter in process of image compression to increase compression ratio and to enhance image compression effectiveness. Image compression by SOFM model is presented and consists of three stages: The first is band-pass filter. The result experiments used Lena.bmp, girl256.bmp, and show compression in block image 16x16 given best compression ratio with a small signal-noise ratio (SNR).

Influence of Neighborhood Forms on the Quality of Pseudorandom Number Generators' Work Based on Cellular Automata

The chapter analyzes modern methods for constructing pseudo-random number generators based on cellular automata. Also analyzes the influence of neighborhood forms on the evolution of the functioning of cellular automata, as well as on the quality of the formation of pseudo-random bit sequences. Based on the use of various forms of the neighborhood for the XOR function, the quality of generators was analyzed using graphical tests and NIST tests. As a result of experimental studies, the optimal dimension of cellular automata and the number of heterogeneous cells were determined, which make it possible to obtain a high-quality pseudo-random bit sequence. The obtained results allowed to formulate a method for constructing high-quality pseudo-random number generators based on cellular automata, as well as to determine the necessary initial conditions for generators. The proposed generators allow to increase the length of the repetition period of a pseudo-random bit sequence.

Image Processing and Pattern Recognition Based on Artificial Models of the Structure and Function of the Retina

The chapter considers principles of construction of retina of the eye. It proposed a system recognition of complex images that models the structure of the retina and the signals at its output. The system is capable of recognizing images and creating new classes. The time impulse description method of images using cellular automata is considered. Images are described by pulse sequences that are created with the help of specially organized cellular automata. The system allows the authors to recognize images of complex shape, which can have an arbitrary location in the field of the visual scene and can have a different scale.