Multilevel Quantum Sperm Whale Metaheuristic for Gray-Level Image Thresholding

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F20%3A10246962" target="_blank" >RIV/61989100:27240/20:10246962 - isvavai.cz</a>

Výsledek na webu

<a href="https://link.springer.com/chapter/10.1007%2F978-981-15-1286-5_69" target="_blank" >https://link.springer.com/chapter/10.1007%2F978-981-15-1286-5_69</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-981-15-1286-5_69" target="_blank" >10.1007/978-981-15-1286-5_69</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Multilevel Quantum Sperm Whale Metaheuristic for Gray-Level Image Thresholding

Popis výsledku v původním jazyce

Image thresholding is a fundamental step in image segmentation. A clever selection of thresholds is a vital step to achieve effective segmentation of images. In this article, we present a new quantum metaheuristic algorithm inspired by the behavior of sperm whales for optimal thresholding of gray-level images. The algorithm is built using many-valued quantum computing principles which offer greater computational advantages. Results are demonstrated on four test images with three threshold levels. The performance of the proposed algorithm has been compared with the qubit encoded quantum-inspired simulated annealing algorithm and the classical sperm whale algorithm with respect to the optimal fitness values and the computational time. Friedman test has been carried out with the competing algorithms to establish the supremacy of the proposed technique. Experimental results indicate the superiority of the proposed method in comparison with the competing methods.

Název v anglickém jazyce

Multilevel Quantum Sperm Whale Metaheuristic for Gray-Level Image Thresholding

Popis výsledku anglicky

Image thresholding is a fundamental step in image segmentation. A clever selection of thresholds is a vital step to achieve effective segmentation of images. In this article, we present a new quantum metaheuristic algorithm inspired by the behavior of sperm whales for optimal thresholding of gray-level images. The algorithm is built using many-valued quantum computing principles which offer greater computational advantages. Results are demonstrated on four test images with three threshold levels. The performance of the proposed algorithm has been compared with the qubit encoded quantum-inspired simulated annealing algorithm and the classical sperm whale algorithm with respect to the optimal fitness values and the computational time. Friedman test has been carried out with the competing algorithms to establish the supremacy of the proposed technique. Experimental results indicate the superiority of the proposed method in comparison with the competing methods.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/EF16_027%2F0008463" target="_blank" >EF16_027/0008463: Věda bez hranic</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2020

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Advances in Intelligent Systems and Computing. Volume 1087

ISBN

978-981-15-1285-8

ISSN

2194-5357

e-ISSN

—

Počet stran výsledku

14

Strana od-do

775-788

Název nakladatele

Springer

Místo vydání

Singapur

Místo konání akce

Ostrava

Datum konání akce

21. 3. 2018

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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