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
A Cellular Fuzzy Associative Memory for Bidimensional Pattern Segmentation / Carnimeo, Leonarda; Giaquinto, A. - In: Proceedings of the 2002 7th IEEE International Workshop on Cellular Neural Networks and Their Applications, CNNA 2002. / [a cura di] Ronald Tetzlaff. - [s.l] : IEEE, 2002. - ISBN 981-238-121-X. - pp. 430-435 (( convegno 7th IEEE Workshop on Cellular Neural Networks & Their Appl. (CNNA02) tenutosi a Frankfurt, Germany nel July, 22-24, 2002 [10.1109/CNNA.2002.1035080].
A Cellular Fuzzy Associative Memory for Bidimensional Pattern Segmentation
CARNIMEO, Leonarda;
2002-01-01
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 purposesI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
