This paper presents an implementation of a modified parallel-pyramidal algorithm for efficient image processing and identification. The method involves the creation of a system model that supports the integration of spatial, temporal and network data to form a dynamic pyramidal-hierarchical network. The paper details vector sorting techniques, Gtransformations for modifying vector elements, and a shifting procedure that facilitates efficient data transformation. The procedures described are integrated into a general data processing sequence that involves iterative application of these methods until the final result is achieved. How the algorithm works is shown in the example of laser beam projection analysis.
This article presents the implementation of a modified parallel-pyramidal algorithm for the efficient processing and identification of images. The method involves creating a systemic model that supports spatial, temporal, and network data integration, forming a dynamic pyramidal-hierarchical network. The article details the techniques for sorting vectors, G-transformations for modifying vector elements, and the shifting procedure that facilitates efficient data transformation. The described procedures are integrated into the overall data processing sequence, which includes the iterative application of these methods until the final result is achieved.
The paper discusses the pyramid methods of direct and inverse Q-transformation. Examples of method implementation based on numerical data transformation are considered. The work is dedicated to the development of a method of pyramid transformation based on contour Q-transformation for encoding and processing images. The method of pyramid Q-transformation and an example of its application are detailed, and the results of its software model are analyzed.
The article discusses the challenges of real-time data processing and analyzes various methods used to solve them, with a focus on image processing. It points out the limitations of existing methods and argues for the need to use more effective and modern technologies, proposing parallel-hierarchical networks as a promising solution. The article provides a detailed description of the structural-functional model of this type of network, which involves cyclically transforming the input data matrix using a "common part" criterion and an array evolution operator until a set of individual elements is formed. The proposed model is expected to improve real-time image recognition and can potentially be applied to other fields by using the "common part" criterion.
This article examines the structures of one of the types of pyramidal networks - parallel-hierarchical networks. The presented material has a dual purpose - applied and cognitive. The first one is of great importance in increasing the "intelligence" of specialized computer tools using a bionic approach. The second one opens completely new possibilities for a deeper understanding of the structure of the brain from the perspective of the cybernetic approach.
This paper describes an approach to solving the problem of fast pattern recognition with image co-ordinate detection and measurement under undefined noise and signal conditions. An analysis of the use of the W-transform method as a basis for image comparison algorithms was carried out. Image comparison algorithms with noise robustness were developed.
The article examines the analysis of the multistage process of correlation interactions in parallel-hierarchical structures for organization of neuro-like calculations. The process of formation of parallel-hierarchical network is considered in detail. The graph-scheme of PH transformation is given. The process of elements formation for five levels of the network is analyzed. It was determined which elements are correlated and decorrelated in time. Based on the analysis, a structural-functional model of correlation interactions of parallel-hierarchical network elements was developed.
An approach to solving the problem of monitoring the surface shape of a radiation spot in real time is presented. An analysis of the use of the cross-sectional method to monitor the shape of the surface of a radiation spot in real time has been carried out. The possibility of using the aspect ratio to solve the problem was considered. Experimental studies of the sectional method and the aspect ratio method are also presented.
KEYWORDS: Telecommunications, Navigation systems, Laser systems engineering, Laser development, Signal processing, Optical filters, Atmospheric optics, Optical communications, Digital signal processing, Computing systems
The article introduces an approach to solving the problem of small beam divergence in data transmission using lasers. A combined model for calculating and classifying laser beam spots is developed, the developed scheme is modeled and the solution speed is analyzed. , the developed method showed good efficiency and can be used for calculating the coordinates of laser beam spots and their further classification. It can be useful in such systems as laser beam profiling systems, fiber optic communication systems, laser navigation and tracking systems in military affairs, and atmospheric optical communication lines.
The methods of processing biomedical images, namely thermal images, are investigated. Algorithms for calculating the temperature and area of the zone of interest in the manual mode operator-computer, as well as in the automatic mode, are specified. Methods of thermal image processing are presented, namely recursive generalized contour preparation and preparation based on histograms of connections. An experimental study of these methods was performed, as well as a comparison of thermal image segmentation methods in manual segmentation modes, using contour preparation-based segmentation, multilevel segmentation based on recursive generalized contour preparation, and automatic segmentation based on connectivity histograms.
KEYWORDS: Photonic integrated circuits, Data compression, Statistical analysis, Associative arrays, Data processing, Data modeling, Computer programming, Data conversion, Binary data, Algorithm development
Basic coding methods for data compression in optical transmission are considered. A parallel-hierarchical transformation is proposed as a means of addressing the shortcomings of the methods considered. Pyramid-linear and pyramid-nonlinear coding at the functional level are given. The corresponding number of elements in the masks was calculated. The efficiency of the developed method compared to known methods was analyzed. The compression ratio and data compression conditions were determined.
KEYWORDS: Signal detection, Image processing, Image analysis, Video, Signal to noise ratio, Interference (communication), Signal processing, Image compression, Switching, Signal generators
The article identifies invariance to image rotation as one of the main problems in image processing. A pyramidal method of generalized spatial processing was proposed as a means to solve the problem specified. The principle of signal processing according to the developed method is presented with an example of its implementation. A comparison of the developed preparation method with the contour preparation method was carried out. As a result, the level of immunity of the developed method to disturbance under Gaussian noise was determined.
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