Path: Top -> Journal -> Jurnal Internasional -> King Saud University -> 2018 -> Volume 30, Issue 4, October

Self-adaptive dragonfly based optimal thresholding for multilevel segmentation of digital images

Journal from gdlhub / 2019-05-24 10:25:07
Oleh : Rakoth Kandan Sambandam, Sasikala Jayaraman, King Saud University
Dibuat : 2019-05-24, dengan 1 file

Keyword : Meta-heuristic algorithms, Dragonfly optimization Multilevel segmentation
Url : http://www.sciencedirect.com/science/article/pii/S1319157816301082
Sumber pengambilan dokumen : WEB

Dragonfly optimization (DFO) is a population based meta-heuristic optimization algorithm that simulates the static and dynamic swarming behaviors of dragonflies. The static swarm comprising less number of dragonflies in a small area for hunting preys, while the dynamic swarm with a large number of dragonflies migrates over long distances; and they represent the exploration and exploitation phases of the DFO. This paper introduces a self adaptive scheme for tuning the DFO parameters and suggests a methodology involving self-adaptive DFO (SADFO) for performing multilevel segmentation of digital images. The multilevel segmentation problem is formulated as an optimization problem and solved using the SADFO. The method optimizes the threshold values through effectively exploring the solution space in obtaining the global best solution. The results of real life and medical images illustrate the performance of the suggested method.

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PropertiNilai Properti
ID Publishergdlhub
OrganisasiKing Saud University
Nama KontakHerti Yani, S.Kom
AlamatJln. Jenderal Sudirman
KotaJambi
DaerahJambi
NegaraIndonesia
Telepon0741-35095
Fax0741-35093
E-mail Administratorelibrarystikom@gmail.com
E-mail CKOelibrarystikom@gmail.com

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