Experiments were carried out to investigate the possibility of training cellular automata to to perform processing. Currently, only binary images are considered, but the space of rule sets is still very large. Various objective functions were considered, and sequential floating forward search used to select good rule sets for a range of tasks, namely: noise filtering, thinning, and convex hulls. Several modifications to the standard CA formulation were made (the B-rule and 2-cycle CAs) which were found to improve performance. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Rosin, P. L. (2005). Training cellular automata for image processing. In Lecture Notes in Computer Science (Vol. 3540, pp. 195–204). Springer Verlag. https://doi.org/10.1007/11499145_22
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