A cellular fuzzy associative memory for bidimensional pattern segmentation

Abstract

In this paper a cellular fuzzy associative memory containing fuzzy rules for gray image fuzzification in automatic vision systems is developed. This cellular processor is viewed as a subsystem of a CNN-based architecture, which aims to store both bidimensional patterns and the rules to process them. After establishing the fuzzy rules which define the fuzzy associative memory for image processing, a CNN behaving as a memory is synthesized to store them. A numerical example is reported to show how the synthesized cellular FAM can process bidimensional patterns for robotic navigation purposes.