Principles of implementation of cellular automata with hexagonal coverage are considered as applied to pattern recognition and image processing based on the Radon transform. Software and hardware implementations of the developed structure are simulated in the Active-HDL environment. The results of finding straight lines and segments and also of image recognition are presented.

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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.

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.