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.
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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