Title :
Training genetically evolving cellular automata for image processing
Author :
Sahota, P. ; Daemi, M.F. ; Elliman, D.G.
Author_Institution :
Dept. of Comput. Sci., Nottingham Univ., UK
Abstract :
The paper describes the use of a genetically controlled automaton model to tackle image processing problems. A generalised system is set up that attempts to discover the precise cellular automaton functions required to solve a given problem. Functions are located with the help of a genetic algorithm, and once trained the system is able to process unseen images. The results have shown that the system correctly solves the task of image edge detection, and that the same procedure may be used for any image processing task
Keywords :
cellular automata; edge detection; genetic algorithms; image processing; image sequences; learning (artificial intelligence); genetic algorithm; genetically controlled automaton model; genetically evolving cellular automata; image edge detection; image processing; training; unseen images; Automata; Automatic control; Computer science; Genetic algorithms; Genetic engineering; Image edge detection; Image processing; Image recognition; Machine intelligence; Pixel;
Conference_Titel :
Speech, Image Processing and Neural Networks, 1994. Proceedings, ISSIPNN '94., 1994 International Symposium on
Print_ISBN :
0-7803-1865-X
DOI :
10.1109/SIPNN.1994.344802
