Training Cellular Automata for Image Processing

  • Paul L. Rosin
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3540)


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.


Root Mean Square Error Root Mean Square Convex Hull Cellular Automaton Cellular Automaton 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Paul L. Rosin
    • 1
  1. 1.Cardiff School of Computer ScienceCardiff UniversityCardiffUK

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