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

Abstract

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.

Enhancing Robot Navigation Efficiency Using Cellular Automata with Active Cells

“…Employing a hexagonal mosaic, as shown in Fig. 9, the navigation possibilities can be enhanced [25,26].…”