Improving a firefly meta-heuristic for multilevel image segmentation using Tsallis entropy

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dc.contributor.authorRODRIGUES, Paulo
dc.contributor.authorLOPES, Guilherme
dc.contributor.authorERDMANN, H. R.
dc.contributor.authorRIBEIRO, M. P.
dc.contributor.authorGIRALDI, G. A.
dc.date.accessioned2019-08-17T20:00:30Z
dc.date.available2019-08-17T20:00:30Z
dc.date.issued2015
dc.description.abstractIn this paper we show that the non-extensive Tsallis entropy, when used as kernel in the bio-inspired firefly algorithm for multi-thresholding in image segmentation, is more efficient than using the traditional crossentropy resented in the literature. The firefly algorithm is a swarm-based meta-heuristic, inspired by fireflies-seeking behavior following their luminescence. We show that the use of more convex kernels, as those based on non-extensive entropy, is more effective at 5 % of significance level than the cross-entropy counterpart when applied in synthetic spaces for searching thresholds in global minimumen
dc.description.firstpage1
dc.description.lastpage20
dc.description.volume1
dc.identifier.citationRODRIGUES, Paulo; LOPES, Guilherme; ERDMANN, H. R.; RIBEIRO, M. P.; GIRALDI, G. A. Improving a firefly meta-heuristic for multilevel image segmentation using Tsallis entropy. Pattern Analysis and Applications (Print), v. 1, p. 1-20, 2015.
dc.identifier.doi10.1007/s10044-015-0450-x
dc.identifier.issn1433-7541
dc.identifier.urihttps://repositorio.fei.edu.br/handle/FEI/1008
dc.identifier.urlhttps://link.springer.com/content/pdf/10.1007%2Fs10044-015-0450-x.pdf
dc.relation.ispartofPattern Analysis and Applications (Print)
dc.rightsAcesso Aberto
dc.subject.otherlanguageFirefly meta-heuristicen
dc.subject.otherlanguageTsallis entropyen
dc.subject.otherlanguageImage segmentationen
dc.subject.otherlanguageOptimizationen
dc.titleImproving a firefly meta-heuristic for multilevel image segmentation using Tsallis entropypt_BR
dc.typeArtigopt_BR
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