A study of a firefly meta-heuristics for multithreshold image segmentation

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Erdmann H.
Lopes L.A.
Wachs-Lopes G.A.
Ribeiro M.P.
Rodrigues P.S.
Computational Vision and Medical Image Processing IV - Proceedings of Eccomas Thematic Conference on Computational Vision and Medical Image Processing, VIPIMAGE 2013
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© 2014 Taylor & Francis Group, London.Thresholding-based image segmentation algorithms are usually developed for a specific set of images because the objective of these algorithms is strongly related to their applications. The binarization of the image is generally preferred over multi-segmentation, mainly because it’s simple and easy to implement. However, in this paper we demonstrate that a scene separation with three threshold levels can be more effective and closer to a manually performed segmentation. Also, we show that similar results can be achieved through a firefly-based meta-heuristic. Finally, we suggest a similarity measure that can be used for the comparison between the distances of the automatic and manual segmentation.