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Image segmentation based on g-un-mms and heuristics. Theoretical background and results

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dc.contributor.author TEODORESCU, Horia-Nicolai
dc.contributor.author RUSU, Mariana
dc.date.accessioned 2021-11-18T13:37:24Z
dc.date.available 2021-11-18T13:37:24Z
dc.date.issued 2013
dc.identifier.citation TEODORESCU, Horia-Nicolai, RUSU, Mariana. Image segmentation based on g-un-mms and heuristics. Theoretical background and results. In: Proceedings of the Romanian Academy, Series A, 2013, V. 14, N. 1, pp. 78–85. en_US
dc.identifier.uri http://repository.utm.md/handle/5014/18119
dc.description.abstract We present the concept of image segmentation based on Gauss - Uniform Noise Mixed Models (GUN-MM) that we also introduce in this paper, the theoretical foundation of the segmentation method based on this model, results of the method on several classes of pictures, and a comparison with other methods. The proposed implementation of the G-UN-MM method has a simple and sound theoretical foundation and is not computationally demanding. It produces in many cases better segmentation results than other methods that are more computationally intensive. en_US
dc.language.iso en en_US
dc.publisher The Publishing House of the Romanian Academy en_US
dc.rights Attribution-NonCommercial-NoDerivs 3.0 United States *
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/us/ *
dc.subject images en_US
dc.subject segmentation en_US
dc.subject statistical models en_US
dc.subject Gauss mixed models en_US
dc.title Image segmentation based on g-un-mms and heuristics. Theoretical background and results en_US
dc.type Article en_US


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