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

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dc.contributor.authorERDMANN, H.
dc.contributor.authorLOPES, L. A.
dc.contributor.authorGuilherme Lopes
dc.contributor.authorRIBEIRO, M. P.
dc.contributor.authorPaulo Rodrigues
dc.contributor.authorOrcidhttps://orcid.org/0000-0003-0873-3236
dc.contributor.authorOrcidhttps://orcid.org/0000-0003-3258-0794
dc.date.accessioned2023-08-26T23:48:37Z
dc.date.available2023-08-26T23:48:37Z
dc.date.issued2014-10-14
dc.description.abstract© 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.
dc.description.firstpage211
dc.description.lastpage218
dc.identifier.citationERDMANN, H.; LOPES, L. A.; LOPES, G.; RIBEIRO, M. P.; RODRIGUES, P. A study of a firefly meta-heuristics for multithreshold image segmentation. Computational Vision and Medical Image Processing IV - Proceedings of Eccomas Thematic Conference on Computational Vision and Medical Image Processing, VIPIMAGE 2013, p. 211-218, 2014.
dc.identifier.urihttps://repositorio.fei.edu.br/handle/FEI/4922
dc.relation.ispartofComputational Vision and Medical Image Processing IV - Proceedings of Eccomas Thematic Conference on Computational Vision and Medical Image Processing, VIPIMAGE 2013
dc.rightsAcesso Restrito
dc.titleA study of a firefly meta-heuristics for multithreshold image segmentation
dc.typeArtigo de evento
fei.scopus.citations1
fei.scopus.eid2-s2.0-84973137581
fei.scopus.subjectImage segmentation algorithm
fei.scopus.subjectManual segmentation
fei.scopus.subjectMeta heuristics
fei.scopus.subjectMetaheuristic
fei.scopus.subjectMulti-segmentation
fei.scopus.subjectMultithreshold
fei.scopus.subjectSimilarity measure
fei.scopus.subjectThreshold levels
fei.scopus.updated2025-02-01
fei.scopus.urlhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84973137581&origin=inward
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