An edge detection method using outer totalistic cellular automata

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dc.contributor.author Amrogowicz, Sebastian
dc.contributor.author Zhao, Yitian
dc.contributor.author Zhao, Yifan
dc.date.accessioned 2016-07-06T12:11:25Z
dc.date.available 2016-07-06T12:11:25Z
dc.date.issued 2016-05-20
dc.identifier.citation Sebastian Amrogowicz, Yitian Zhao, Yifan Zhao, An edge detection method using Outer totalistic cellular automata, Neurocomputing, Vol 214, 19 November 2016, pp.643-653 en_UK
dc.identifier.issn 0925-2312
dc.identifier.uri http://dx.doi.org/10.1016/j.neucom.2016.05.092
dc.identifier.uri http://dspace.lib.cranfield.ac.uk/handle/1826/10098
dc.description.abstract A number of Cellular Automata (CA)-based edge detectors have been developed recently due to the simplicity of the model and the potential for simultaneous removal of different types of noise in the process of detection. This paper introduced a novel edge detector using Outer Totalistic Cellular Automata. Its performance has been compared with other recently developed CA-based edge detectors, in addition to some classic methods, through testing images from a public library. Visual and quantitative measurement of similarity with manually marked correct edges confirmed the superiority of the proposed method over conventional and state-of-the-art CA-based edge detectors. en_UK
dc.language.iso en en_UK
dc.publisher Elsevier en_UK
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Cellular Automata en_UK
dc.subject Edge detection en_UK
dc.subject Figure of merit en_UK
dc.subject Totalistic Cellular Automata en_UK
dc.title An edge detection method using outer totalistic cellular automata en_UK
dc.type Article en_UK


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